Who We Are

Babylist is the leading registry, e-commerce, and content platform for growing families. More than 9 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, trusted guidance, and expert product recommendations for new parents and the people who love them. What began as a universal registry has grown into a full ecosystem for new parents, including the Babylist Shop, Babylist Health, and a flagship showroom in Los Angeles. Hundreds of brands in baby and beyond partner with Babylist to engage meaningfully with families during one of life’s most important transitions. With over $1 billion in annual GMV, and more than $500 million in 2024 revenue, Babylist is reshaping the $320 billion baby product industry. We’re helping parents feel confident, connected, and cared for at every step. As we build the generational brand in baby, our mission remains simple: to connect growing families with everything they need to thrive.To learn more, visit www.babylist.com.

Our Ways of Working

Babylist is remote-first with team members across the U.S. and Canada who move fast, think smart, and use AI as part of how they work every day — not as an experiment, as an expectation. We come together twice a year to build the relationships behind the work, and we hire people who are genuinely excited about what's possible and prove it through how they show up.

How We Build

Babylist is in the middle of a fundamental shift in how software gets made, and we are not tiptoeing into it. We are rebuilding our engineering culture around a simple belief: AI changes everything. How teams are structured, how decisions get made, how fast ideas become working software. Our engineers own problems end to end, working directly with product, design, and business partners with short feedback loops and real stakeholder access. We ship, learn, and iterate fast. When something is not working, we throw it out and start over — project failure and personal failure are not the same thing here. AI tools are as natural to our workflow as an IDE or version control. We are not exploring this, we are living it. Our engineers use AI to explore tradeoffs, pressure-test designs, and move from problem to solution in hours instead of days. They generate code with AI so they can stay focused on the decisions that actually require human judgment — not the routine ones. More velocity means more time for craft: better test coverage, stronger architecture, and deeper customer understanding. We hold ourselves to a higher quality bar because of AI, not in spite of it. We are building this playbook in real time, and we are looking for people who want to build it with us. If you have already changed how you work because of AI — or you are ready to — and you care more about shipping something great than following a prescribed process, we should talk.

Our Tech Stack 

• React, Native iOS and Android
• Ruby on Rails
• AWS, Terraform
• MySQL
• Sidekiq
• Redis
• Shopify

What the Role Is

As Babylist’s Senior Engineering Manager, Machine Learning & Discovery+Site Monetization, you’ll lead the team driving the next era of our machine learning and personalization efforts across the product. This is a hands-on leadership role for a manager who remains technically fluent while scaling people, systems, and impact. You’ll manage and grow a high-performing ML-focused pod spanning product recommendations, search, PLPs, and site monetization, with a clear mandate: maximize revenue and user value across surface areas through personalization.

You’ll guide the team on technical direction behind our homepage feed, “add next” experience, and other core personalization surfaces, while building the foundations for long-term ML excellence at Babylist.

Who You Are

• 3+ years of experience as a front-line manager delivering production-grade software or ML systems
• 5+ years of experience as an individual contributor in ML or Data Science, plus proven experience leading teams that build end-to-end machine learning systems, ideally in personalization, recommendations, or consumer-facing ML products
• Deep familiarity with the Python ML ecosystem (e.g., pandas, sklearn, xgboost, PyTorch) and comfortable reviewing designs, unblocking technical challenges, and setting high technical standards
• Experience supervising ML Engineers and/or Data Scientists; bonus points for experience managing Software Engineers
• Strong understanding of the full ML lifecycle, including data pipelines, workflow orchestration (e.g., Airflow), deployment, monitoring, and iteration in production
• Product-minded: passionate about technology, but primarily motivated by solving real user problems and driving business impact
• Experience working with large-scale, real-time or near-real-time data systems
• Comfortable owning and evolving the ML tech stack end-to-end, from data and modeling through production systems
• Background in consumer-facing products; experience in e-commerce, marketplaces, or complex user journeys is strongly preferred
• You're genuinely excited about what AI can do - not just as a concept, but as something you want to get your hands on. At Babylist, every team uses AI daily, and we're looking for people who lean in.

How You Will Make An Impact

• Build and lead the ML & personalization function: Hire, mentor, and support a multidisciplinary team (Machine Learning Engineers, Software Engineers, Product Manager, and occasional Designer), shaping the roadmap, standards, and culture for ML at Babylist
• Own high-impact ML initiatives: Deliver personalization systems that improve discovery, engagement, and monetization across key surfaces, directly impacting business outcomes
• Set technical and algorithmic direction: Define modeling approaches, data strategy, and system architecture in partnership with senior technical leaders, balancing experimentation with scalable execution
• Be hands-on when needed: Review ML/DS designs and code, build proof-of-concept models, and conduct your own data science research to de-risk ideas and accelerate progress
• Develop talent: Coach engineers on technical growth, career progression, and performance, combining strong technical standards with empowerment
• Drive cross-functional alignment: Partner closely with Product, Design, Analytics Engineering, and Data to translate ambiguous business problems into clear technical direction
• Understand the full funnel: Develop a deep understanding of Babylist’s user journeys, user feedback loops, and financial models — and how ML systems influence them end-to-end

About Compensation

We use a market-based approach to compensation. The starting salary range for this role is:

USD - $250,000 to $308,000
CAD - $230,000 to $288,000

Your starting salary will be based on your location, experience, and qualifications, with increases over time tied to performance, role growth, and internal pay equity.

Why You Will Love Working At Babylist

Our Culture

• We work with focus and intention, then step away to recharge
• We believe in exceptional management and invest in tools and opportunities to connect with colleagues
• We build products that positively impact millions of people's lives
• AI tools are as natural to how we work as your IDE or version control — we're not exploring this, we're living it.

Growth & Development

• Competitive pay and meaningful opportunities for career advancement
• We believe technology and data can solve hard problems
• We're committed to career progression and performance-based advancement

Compensation & Benefits

• Competitive salary with equity and bonus opportunities
• Company-paid medical, dental, and vision insurance
• Retirement savings plan with company matching and flexible spending accounts
• Generous paid parental leave and PTO
• Remote work stipend to set up your office
• Perks for physical, mental, and emotional health, parenting, childcare, and financial planning

Important Notices

Recorded Interviews Babylist uses an interview recording tool to record and transcribe interviews for evaluation purposes in accordance with applicable privacy laws. By participating in an interview, you consent to this recording and transcription.

Interview Integrity At Babylist, every team uses AI daily and we love it. During interviews though, we want to see you — your thinking, your problem-solving, your creativity. All interviews and assessments should be completed independently without AI tools or third-party assistance unless we tell you otherwise. We'll always be clear when AI is welcome. Misrepresentation during the process may result in removal from consideration.

Protect Yourself from Scams All official communication comes from the Babylist Talent Team via @babylist.com email addresses. We will never ask for payment, bank information, or personal financial details. If you receive outreach via WhatsApp, Telegram, or a non-Babylist email, it's not us. Verify open roles on our careers page.

Connections at Babylist In line with our conflict of interest policy, please let us know if you have a family member or close personal relationship with a current Babylist employee. This helps us keep our process fair for everyone.

Text Message Updates You may opt in to receive SMS updates about your application. Opting out won't affect your status. Message and data rates may apply. Reply STOP to unsubscribe or HELP for assistance. See our Privacy Policy for details.

CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

About the Team: Mission Engineering at CHAOS turns simulation output into decisions. We run large-scale modeling and simulation campaigns across all warfighting domains and the full kill chain, against named threats, in operationally relevant scenarios, at the speed engineering, operational, and customer teams actually need. Every CHAOS engineering trade, pursuit, and customer engagement is anchored in rigorous, physics-based, tactically relevant, and statistically valid analysis, and we're scaling the function to meet that bar across a growing product portfolio.

About the Role: On the Mission Engineering team at CHAOS, you will design, develop, execute, analyze, and validate models and simulations to deliver operational analysis and system performance assessment across defense, national security, and commercial programs. You will have freedom to move rapidly and use your expertise to apply rigorous statistical methods to analyze simulation outcomes, quantify system effectiveness, and communicate actionable insights to technical teams, leadership, and customers. Your work will directly inform critical decisions around sensor performance, mission planning, weapon effectiveness, and platform capability evaluation.

This is a foundational hire. You will shape how CHAOS does mission analysis from day one, and you will have the freedom to move fast.

What You'll Do:

• Scope, plan, and execute modeling and simulation efforts and studies aligned to program objectives, managing your competing priorities and timelines effectively.
• Develop, configure, and execute analysis using mission-level models and simulations such as AFSIM, ESAMS, Brawler, Ansys STK, and/or physics-based models to evaluate system and platform performance in operationally relevant scenarios.
• Build and refine models of sensors, communications systems, aircraft (including unmanned), weapons, and spacecraft within mission-level simulation frameworks.
• Architect, implement, and validate models of both blue and red systems, sensors, communications, weapons, aircraft, spacecraft, and ground/maritime platforms, within mission- and engagement-level simulation frameworks.
• Define and apply rigorous statistical methodologies to simulation results to quantify measures of effectiveness and performance to produce relevant and defensible findings for internal and external stakeholders.
• Develop and maintain Python-based analysis tools and pipelines for data processing, statistical analysis, and visualization.
• Implement technical methodology, simulation best practices, and customer engagement.
• Document methodology, assumptions, and findings in technical reports and briefing materials, including data visualizations, and present results to both technical and non-technical audiences.
• Partner with engineering, product, growth, and customer teams to translate operational questions into well-structured analytical approaches and shape new business pursuits. Push back when the framing is wrong.

Minimum Requirements:

• Bachelor's degree or higher in Computer Science, Aerospace/Software/Computer Engineering, Data Science, Statistics, Mathematics, Operations Research, Physics, or a related field.
• 5+ years of experience supporting defense, intelligence, or advanced technology programs through industry or government employment.
• Demonstrated track record leading mission-level operations analysis studies and delivering decision-quality results to senior engineering and customer stakeholders.
• Extensive direct experience with combat simulations such as AFSIM, ESAMS, Brawler, Ansys STK, or equivalent, including ownership of rigorous methodology, not just execution.
• Significant experience developing analytical tools and applying rigorous statistical methods to interpret and present results.
• Strong proficiency in Python and MATLAB, including standard scientific computing libraries (such as Pandas, Polars, NumPy, SciPy, Scikit-Learn, Matplotlib, Seaborn, CuPy, or PyTorch).
• Exceptional data visualization skills and comfort developing CONOPS/OV-1 visuals and briefing packages.
• Proficiency with software development practices including version control and leveraging/validating outputs of AI-assisted coding tools.
• Demonstrated ability to lead analytical efforts and deliver products with minimal oversight, including leading projects and studies.
• Comfortable working on Linux-based systems and writing scalable scripts and software.
• Exceptional written and verbal communication skills, including experience briefing flag/general officer or SES-level audiences.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance 

Preferred Requirements:

• Active TS/SCI clearance.
• Recognized expertise analyzing the full kill chain (find, fix, track, target, engage, assess) across multiple domains, including air-to-air, air-to-surface, surface-to-air, space, and electronic warfare engagements.
• Deep expertise in sensor performance analysis (especially radar) and in developing and validating models of sensors, communications, weapons, aircraft, spacecraft, or ground/maritime systems in mission-level simulation environments such as AFSIM or Ansys STK.
• Experience leading study teams or technical working groups across organizations, including model accreditation, V&V efforts, or threat-informed scenario development.
• Experience designing and analyzing large-scale Monte Carlo and DOE-driven simulation campaigns supporting system effectiveness or kill chain assessment.
• Exposure to Distributed Interactive Simulation (DIS) networking and visualization tools such as MAK VR-Forces, SIMDIS, or similar.
• Experience supporting rapid development programs across DoD services, DARPA, ONR, AFRL, COCOMs, the acquisition community, or commercial advanced technology programs.
• Experience supporting capture and positioning activities (RFI/RFP responses, white papers, technical exchanges) and shaping new business pursuits.

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 250 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

About the Team: Mission Engineering at CHAOS turns simulation output into decisions. We run large-scale modeling and simulation campaigns across all warfighting domains and the full kill chain, against named threats, in operationally relevant scenarios, at the speed engineering, operational, and customer teams actually need. Every CHAOS engineering trade, pursuit, and customer engagement is anchored in rigorous, physics-based, tactically relevant, and statistically valid analysis, and we're scaling the function to meet that bar across a growing product portfolio.

About the Role: You will own statistical methodology for the Mission Engineering team at CHAOS. You'll design experimental constructs that extract meaningful signals from broad trade studies and computationally expensive simulation runs, build the analytical pipelines the team relies on, push the methodological state of the art on how we characterize uncertainty, build surrogate models, and communicate quantitative results to decision-makers. You will work shoulder-to-shoulder with engineers and experts in every domain to ensure that simulated, experimental, and tactical results presented by CHAOS are rigorous, reproducible, and actually deliver answers that our teams, customers, and partners need

This is a foundational hire. You will have the freedom to move fast and set the standards for how CHAOS does quantitative analysis from day one.

What You'll Do:

• Design rigorous experimental constructs (DOE, space-filling designs, adaptive sampling, sequential experimentation) for large-scale simulation campaigns, getting maximum signal per simulation hour across operationally relevant trade spaces.
• Apply advanced statistical methods (such as regression modeling, Bayesian inference, surrogate/metamodeling, sensitivity analysis, uncertainty quantification, and beyond) to simulation output to produce decision-quality conclusions.
• Build and own scalable Python-based data pipelines for ingestion, processing, statistical analysis, and visualization of large simulation datasets.
• Develop ML and statistical surrogate models that accelerate analysis, enable real-time trade studies, and feed mission planning applications.
• Set team standards for data management, reproducibility, and statistical rigor (such as code review, methodology validation, and documentation practices).
• Translate operational and engineering questions into well-structured analytical approaches alongside M&S engineers, threat SMEs, and program staff. Push back when the framing is wrong.
• Author technical reports and briefing materials with clear, honest data visualizations; present quantitative results to senior technical and non-technical audiences in language they can act on.
• Mentor peers and cross-functional teams on experimental design, statistical methodology, and reproducible analysis.
• Support programs spanning DoD services, DARPA, intelligence community, and commercial customers.

Required Qualifications:

• Bachelor's degree or higher in Statistics, Data Science, Mathematics, Artificial Intelligence, a related quantitative field, or equivalent demonstrated expertise in modern statistical methodology.
• 7+ years applying advanced statistical and data science methods, ideally supporting defense, intelligence, or advanced technology programs.
• Deep working expertise in experimental design, regression and Bayesian methods, uncertainty quantification, and surrogate modeling, not just textbook familiarity.
• Strong proficiency working in Python, including scientific computing and ML libraries (especially Pandas, Polars, NumPy, SciPy, Scikit-Learn, Statsmodels, PyMC, Matplotlib, Seaborn, CuPy, PyTorch), and exposure to MATLAB or R.
• Demonstrated experience building scalable analytical pipelines for large datasets, including comfort with terabyte-scale data and modern dataframe tooling.
• Exceptional data visualization skills and the ability to develop briefing-quality technical products.
• Strong software development practices: version control, code review, reproducible workflows, and informed use of AI-assisted coding tools.
• Track record of working independently, taking ownership of ambiguous problems, and delivering with minimal oversight.
• Comfortable working with Linux operating systems and writing scalable scripts/software.
• Exceptional written and verbal communication skills, especially in translating quantitative approaches and results for non-technical audiences.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance.

Preferred Qualifications:

• Master's or PhD in Statistics, Data Science, Mathematics, Artificial Intelligence, or a related quantitative field.
• Direct experience applying statistical methods to outputs from military simulations including high fidelity engineering models, war games, and engagement or mission-level combat simulations such as AFSIM, ESAMS, Brawler, or Ansys STK.
• Expertise designing and analyzing large-scale Monte Carlo and DOE-driven simulation campaigns supporting full kill chain or system effectiveness assessment.
• Experience in developing surrogate models, simulations, machine learning, or artificial intelligence models for engineering and operations analysis applications.
• Familiarity with sensor performance analysis (radar, EO/IR, RF, acoustic), weapon effectiveness analysis, or mission-level engagement analysis.
• Experience with HPC environments and distributed computing frameworks (including scalable cloud services and GPU-accelerated computing).
• Leadership experience: mentoring or leading project teams through complex analytical efforts.
• Substantial experience in communicating statistical methods to both technical and non-technical stakeholders and decisionmakers.
• Experience supporting rapid development programs for DoD contractors, combatant commands, research labs, and acquisition communities.
• Active TS/SCI clearance.

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 250 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

Local or 100% Remote

About Point

✨ Real Impact, Real People: Our mission at Point is to make homeownership more valuable and accessible. Your work directly helps homeowners access their wealth, achieve financial flexibility, and realize life changing goals.

✨ Funding: With over $175M raised from top investors like Andreessen Horowitz, WestCap, Greylock, and Prudential, we’re scaling fast! You have the opportunity to join us at a pivotal stage.

✨ Game-changing Product: We're building a category defining company in home equity. We’ve earned a 4.7 Trustpilot rating and an A+ from the BBB, a testament to the value we provide to our 20,000+ customers.

✨ Great Place to Work: Our employees love working here! We are a Certified Great Place to Work and a Fortune Best Workplaces in the Bay Area.

✨ Remote First Culture, Genuine Connection: Work from anywhere in the U.S., while staying closely connected through virtual collaboration, team gatherings, and a people-first culture.

About the role

We are seeking a Senior Data Scientist to join our growing data team. You will be responsible for building and deploying machine learning models to support marketing, customer engagement, and core business use cases. You will also monitor model performance, identify and mitigate model deterioration, forecast business outcomes, and maintain high-quality datasets. The role is not limited to working on machine learning and model development and will also include, but not limited to advanced analytics projects such as root-cause analysis, identifying trends in data and building time-series projections.

This is an excellent opportunity for someone advanced in their data science career to enhance their skills in applied machine learning while working closely with other senior data scientists, engineers, and cross-functional stakeholders.

Your responsibilities

• Model Development: Design, train, and deploy machine learning models to solve marketing, forecasting, and operational problems.
• Model Monitoring: Track model performance, detect drift or deterioration, and assist in implementing corrective measures.
• Forecasting & Insights: Develop time-series forecasts and performance dashboards that inform marketing strategies and broader business decisions.
• Data Management: Clean, transform, and maintain structured datasets to ensure reliable inputs for analytics and modeling.
• Collaboration: Partner with marketing, product, and business teams to translate requirements into data-driven solutions.
• Documentation & Reporting: Produce clear documentation of models, data pipelines, and processes; communicate insights to technical and non-technical stakeholders.

About you

• 4–5 years of hands-on experience in data science, applied statistics, or machine learning (internships and projects count).
• Familiarity and experience working with AI toolkits such as Claude or Gemini or similar.
• Strong foundation in Python (Pandas, NumPy, scikit-learn; PyTorch or TensorFlow a plus).
• Familiarity with SQL for data extraction and transformation.
• Experience with basic machine learning workflows: preprocessing, feature engineering, model training, validation, and monitoring.
• Understanding of data visualization tools (e.g., Tableau, Power BI, or Python libraries like Matplotlib/Seaborn).
• Curiosity and eagerness to learn — especially around model monitoring, forecasting, and marketing analytics.
• Excellent problem-solving skills and ability to communicate insights clearly.
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field. A Master’s degree is a plus.
• Advanced knowledge of AI tools
• Expertise on BI dashboarding tools such as Sigma or Tableau preferred
• Strong Excel skills

Our benefits 

• Generous health benefits: We provide comprehensive medical, dental, and vision plans with options for flexible spending accounts (FSA) and health savings accounts (HSA).
• Unlimited paid time off: Recharge with unlimited paid time off and 10 company holidays. 
• Flexible remote and onsite work: Our teams work from many different locations and time zones. We support fully remote work and also have an amazing in-person environment in our downtown Palo Alto, CA HQ. 
• Fully paid parental leave: Point will supplement state Paid Family Leave (PFL) so employees receive 100% of their regular base pay, plus two additional weeks of fully paid leave after state PFL ends. In states without PFL, Point offers up to 8 weeks of paid parental leave. In addition, employees also receive 4 weeks of fully paid transition time, during which you may work 2–3 days per week while receiving full base pay.
• Equity: We offer meaningful equity because we believe in sharing the value you help create. Your contributions directly impact our growth, and your equity gives you a stake in our future success. 
• Financial wellness:  We provide 401K retirement plans for employees as well as guaranteed life insurance and short- and long-term disability coverage. 
• Extra work/life benefits: We provide monthly stipends for internet, mobile plans, wellness perks, a one-time home office reimbursement, and company provided equipment including a MacBook and monitor.

Compensation at Point will be determined by skills, experience, and geographic location. Point has identified the expected annual base salary for this role at this level based on the market by tiers (Region | Location | Market Salary):

• Tier 1 | San Francisco Bay Area, New York, and Seattle | $179,550 - $198,450
• Tier 2 | Chicago, Austin, Denver, Boston, Washington DC, San Diego, Portland, Sacramento, Philadelphia, Los Angeles & Santa Barbara | $164,350 - $181,65
• Tier 3 | All other US metro areas | $156,750 - $173,250

This does not include any other potential components of the compensation package, including equity, benefits, and perks outlined above. At the launch of each position, we benchmark compensation to the appropriate role and level utilizing competitive compensation data from various data sources as references. At the offer stage, we use the signal we received from our interviews, coupled with your experience, location, and other job-related factors, to determine final compensation.

Location Requirement: This is a remote position. However, candidates must reside in one of Point’s states of operation: AL, AZ, AR, CA, CO, CT, DC, FL, GA, IL, KS, KY, MA, MD, MI, MN, MO, NH, NV, NJ, NY, NC, OH, OR, PA, SC, TN, TX, UT, VA, WA, WI.

Point is proud to be an equal-opportunity employer. We provide employment opportunities regardless of age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, veteran status, or any other protected class. Each individual at Point brings their own perspectives, work experiences, lifestyles, and cultures with them, and we believe that a more diverse team creates more innovative products, provides better services to customers, and helps us all grow and learn. 

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Inovalon is a leading cloud-based healthcare technology company that leverages data analytics and AI to drive meaningful improvements across the healthcare ecosystem. The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon’s central AI and machine learning hub. This team partners with Provider, Payer, and Pharmacy business units to identify, build, and deploy AI solutions that improve clinical and operational outcomes at scale. 

In this role, you will contribute to both classical machine learning and generative AI applications, including LLM-based and agentic solutions. You will work across the full model development lifecycle on a modern, cloud-native AWS stack, collaborating closely with AI Product Managers and a distributed team of senior engineers across the U.S. and India. 

Key Responsibilities

• Design, train, and deploy machine learning models spanning classical ML (classification, regression, clustering, time-series) and generative AI use cases including LLM-based and agentic applications. 
• Build and maintain cloud-native solutions on AWS using containerized architectures (Docker, Kubernetes) to support scalable model serving and data pipelines. 
• Own and contribute to the full Model Development Lifecycle (MDLC), including dataset versioning, model versioning, model registry management, and model evaluation frameworks. 
• Develop and integrate Python-based ML components that work seamlessly with existing product platforms across multiple business units. 
• Collaborate with AI Product Managers across the Insights BU and partner business units (Provider, Payer, Pharmacy) to translate business needs into AI solutions. 
• Apply neural networks and deep learning techniques using PyTorch for appropriate use cases alongside scikit-learn-based classical approaches. 
• Write robust, production-ready code following engineering best practices; participate in code and design reviews. 
• Leverage AI coding tools (such as Claude Code or equivalent) as part of your daily development workflow to improve velocity and code quality. 
• Mentor junior engineers and contribute to team knowledge-sharing around ML best practices, tooling, and architecture decisions. 
• Support integration of frontend components into ML-powered features where applicable. 
• Contribute to retrospectives and team process improvements; actively participate in sprint planning and end-of-iteration demos. 
• Adhere to all HIPAA, data governance, confidentiality, and regulatory requirements in all aspects of work. 
• Maintain compliance with Inovalon’s policies, procedures, and mission statement, fulfilling responsibilities that support operational and financial success. 

Qualifications

Required 

• Minimum 5 years of software development experience with a strong foundation in machine learning fundamentals and model training. 
• Expert-level Python proficiency; Python is the team’s primary language and is the highest-priority technical requirement. 
• Hands-on experience building and deploying classical ML models in production using scikit-learn. 
• Demonstrated experience with generative AI, LLMs, or agentic application development. 
• Proficiency with PyTorch and neural network architectures. 
• Practical knowledge of the Model Development Lifecycle (MDLC): dataset versioning, model versioning, model registry, and model evaluation. 
• AWS cloud experience, including deploying and managing cloud-native workloads. 
• Containerization experience with Docker and/or Kubernetes. 
• Strong problem-solving ability; demonstrated capacity to work independently and take ownership of complex technical challenges. 
• Daily usage of AI-assisted coding tools (e.g., Claude Code, GitHub Copilot, or similar) as part of standard development workflow. 

Preferred 

• Experience with database technologies (SQL or NoSQL); familiarity with data pipeline tooling. 
• Frontend development skills to support full-stack ML feature work. 
• Healthcare domain experience or exposure to HIPAA-regulated environments. 

Education 

• Bachelor’s degree in Computer Science, Data Science, Software Engineering, or a related technical field required. 
• Master’s degree or PhD in Computer Science, Machine Learning, or equivalent practical experience preferred. 

Physical Demands and Work Environment 

• Sedentary work (i.e., sitting for long periods of time). 
• Exerting up to 10 pounds of force occasionally and/or a negligible amount of force. 
• Subject to inside environmental conditions. 
• Travel for this position will include less than 10% locally, usually for training purposes. 

ABOUT THE TEAM

Anduril's Air & Missile Defense Radar team develops cutting-edge tracking algorithms and software systems that detect, track, and characterize airborne threats in real-time. We're building the next generation of tracking intelligence capabilities—automated analysis systems that understand tracking performance, identify failure modes, and continuously improve our algorithms through data-driven insights.

This role sits at the intersection of ML engineering and tracking domain expertise. You'll build end-to-end pipelines that ingest tracking algorithm telemetry, analyze correlation failures and performance anomalies, train models to automate root cause analysis, and deploy production tools that help engineers ask questions like "why didn't track X and track Y associate?" We don't just track targets; we track our tracking systems and make them smarter.

WHAT YOU'LL DO

• Own tracking intelligence infrastructure end-to-end: Build the platform for ingesting tracking algorithm telemetry (hypotheses, scores, gains, association decisions), feature engineering performance metrics, training analysis models, and deploying them into production
• Automate tracking analysis: Develop ML models that identify correlation failures, track quality degradation, and root causes for tracking anomalies—replacing manual deep-dive investigations with scalable automated insights
• Build autotuning capabilities: Create systems that recognize incoming data characteristics and automatically adjust tracking algorithm parameters, frame rates, and model configurations for optimal performance
• Design human-in-the-loop tools: Build interfaces and query services that let engineers ask natural questions about tracking behavior and get data-driven answers backed by your models
• Exploit tracking telemetry: Instrument C++ tracking algorithms with appropriate logging (working with platform engineers), then marshal that data into consistent formats for analysis and model training
• Deploy in constrained environments: Package and deploy models for air-gapped systems with no external connectivity, following security scanning requirements where ML models are treated as data artifacts
• Manage the ML lifecycle: Handle data catalogs, ground truth labeling, model registries, versioning, and validation—ensuring models improve tracking performance in measurable ways
• Bridge domains: Translate between tracking algorithm fundamentals (Kalman filters, data association, multi-hypothesis tracking) and ML/data science techniques to build solutions that actually work
• Drive make/build decisions: Evaluate when to build custom models vs. leverage existing ML capabilities, selecting appropriate algorithm architectures for tracking intelligence problems
• Work hands-on-keyboard: This is a one-person show initially—you'll architect, code, deploy, and iterate rapidly using modern Python-based ML tooling

REQUIRED QUALIFICATIONS

• 3+ years of experience with a strong mix of ML engineering and data science—you've built models AND deployed them into production systems
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Experience with MLOps practices: data pipelines, feature engineering, model versioning, experiment tracking, and deployment workflows
• Familiarity with ML infrastructure tooling (MLflow, Dagster/Airflow, or similar orchestration tools)
• Understanding of tracking, estimation, or filtering algorithms (Kalman filters, data association techniques)—you need to understand what tracking algorithms output and why they make the decisions they do
• Ability to work with streaming time-series data and engineer features from algorithm telemetry
• Experience building data catalogs, managing ground truth labels, and validating model performance
• Strong software engineering fundamentals—you can build maintainable, production-quality code independently
• Comfortable working in C++ environments enough to add instrumentation/logging (no deep algorithm development required)
• Ability to obtain and maintain a U.S. Top Secret SCI security clearance

PREFERRED QUALIFICATIONS

• Experience deploying ML models in edge, embedded, or air-gapped environments with security constraints
• Background in defense, aerospace, or sensor systems
• Familiarity with containerization (Docker, Kubernetes) for model serving and deployment
• Experience with anomaly detection, root cause analysis, or automated diagnostics systems
• Knowledge of AutoML, hyperparameter tuning, or online learning techniques
• Understanding of radar systems, sensor fusion, or signal processing
• Experience building conversational or query interfaces for technical systems
• Familiarity with model registries and model-as-data artifact management
• Experience with distributed data processing (Spark, Dask) for large-scale telemetry analysis
• Formal coursework or training in MLOps, data science, or estimation theory
• Active U.S. Top Secret SCI clearance

About the opportunity

We are looking for a Data Scientist who will turn data into insights and build models that drive meaningful business outcomes. You will work closely with cross-functional stakeholders to understand problems, design analytical solutions, and deploy data products that scale.

What to expect?

• Collect, clean, and analyze structured and unstructured data.
• Develop predictive models, statistical analyses, and machine learning algorithms.
• Build dashboards, reports, and data visualizations to communicate insights.
• Collaborate with engineering to deploy models into production environments.
• Perform exploratory data analysis (EDA) to identify trends and opportunities.
• Conduct A/B testing and design experiments to measure feature performance.
• Document methodologies and ensure reproducibility of analytical work.
• Contribute to end-to-end machine learning workflows, including model training,  validation, and deployment, working with established tools and patterns and with support from engineering.
• Monitor model performance and data quality, and update models as needed.

What do you need to be successful?

Required

• Bachelor’s or Master’s in Data Science, Computer Science, Statistics, Mathematics, or related field.
• Strong proficiency in Python (pandas, scikit-learn, NumPy).
• Experience using SQL to work with analytical databases and data warehouses.
• Solid understanding of statistical modeling, model evaluation, and experimental methods.
• Familiarity with machine learning techniques (regression, classification, clustering, etc.).
• Hands-on experience building and running machine learning models in production or production-like environments.
• Experience building dashboards with tools like Tableau, or similar.
• Strong analytical and problem-solving skills.
• Ability to balance analytical rigor with practical delivery.
• Excellent communication skills with the ability to translate data insights into business actions.

Preferred    

• Familiarity with workflow orchestration or model lifecycle tools (e.g., Airflow, MLflow) at a practical, working level.
• Implement practical model deployment approaches (e.g., batch inference, scheduled retraining) using existing team tools and patterns.
• Experience with cloud platforms (AWS, or similar).
• Knowledge of ML Ops tools (MLflow, Airflow, or similar).
• Exposure to big data technologies (Redshift, Snowflake).
• Experience working in agile environments.

What's in it for you?

• Join an ambitious tech company reshaping the way people build digital experiences
• Full-time employees receive Stock Options for the opportunity to share in the success of our company
• Comprehensive healthcare package covering 100% of monthly health premiums for employees and 85% of costs for your dependents. 
• Fertility and family building benefits, including a lifetime reimbursable wallet to support your growing family.
• We value Work-Life balance and You Time! A generous amount of paid time off, including vacation days, sick days, compassion days for loss,  education days, and volunteer days
• Company paid parental leave to care for and focus on your growing family 
• Use your personal annual education budget to improve your skills and grow in your career
• Enjoy a full range of virtual and in-person events, including workshops, guest speakers, and fun team activities, supporting learning and networking exchange beyond the usual work duties 
• An annual wellbeing stipend to care for your physical, financial, or emotional health
• A monthly communication stipend and phone hardware upgrade reimbursement.
• New hire office equipment stipend for hybrid or distributed employees. Get the gear you need to work at your best.

This role will need to be conducted in a state in which we are currently registered to do business. In addition, this position is not eligible for visa sponsorship. Applicants must be authorized to work without the need for visa sponsorship by the start date of employment.

This position is eligible for equity awards in accordance with the terms of Contentful’s equity plans.

The application deadline is 05/21/2026

Colorado Salary Statement: The salary range displayed is specifically for those potential hires who will work or reside in the state of Colorado if selected for the role. Any offered salary is determined based on internal equity, internal salary ranges, market data/ranges, applicant's skills and prior relevant experience, certain degrees and certifications (e.g. JD/technology), for example.

Colorado Salary: $136,000-$184,000

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

About the role:

We are looking for a motivated Data Science Intern to join our team. This role offers hands-on experience working with real-world data, building models, and supporting data-driven decision-making. You will collaborate with data scientists, engineers, and business stakeholders to solve meaningful problems.

What You'll Do :

• Collect, clean, and preprocess structured and unstructured data
• Perform exploratory data analysis to identify trends and insights
• Build and evaluate machine learning models under guidance
• Develop data visualizations and dashboards to communicate findings
• Assist in deploying models and monitoring their performance
• Work with large datasets using tools like Python, SQL, and cloud platforms
• Document processes, experiments, and results clearly
• Participate in team demos, feedback sessions, and learning opportunities.
• This role provides mentorship and exposure to customer-facing technical problem solving in a fast-moving AI/Product environment.

What We're Looking For:

• Enrolled in a Bachelor’s or Master’s degree program in Computer Science, Engineering, or a related field.
• Experience writing code in Python (or another general-purpose language).
• Strong interest in artificial intelligence, machine learning, or software engineering.
• Basic understanding of statistics and machine learning concepts
• Familiarity with libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow/PyTorch
• Experience with SQL and working with databases
• Strong analytical and problem-solving skills
• Excellent communication skills and willingness to collaborate with teammates and customers.

Nice-to-Haves

• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn)
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Knowledge of version control (Git)
• Exposure to big data tools (Spark, Hadoop) is a plus

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.com.

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

[Location: remote-friendly or any office location - SF, LA, CHI, NY]

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Location: US remote-friendly

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote

The Team

The Machine Learning Platform team builds the foundational technology that scales machine learning innovation across Upstart. As a Principal Machine Learning Engineer, you will work at the intersection of applied ML and platform engineering—collaborating closely with Research Scientists, Data Scientists, and ML Platform Engineers to design tools and systems that accelerate model development to ultimately improve predictive accuracy. Success in this role requires deep knowledge of ML throughout the entire modeling lifecycle - from data preparation to training and deployment to production.

In this role, you will lead engineering initiatives that turn high-impact modeling needs into scalable, reusable infrastructure. This includes building a unified embeddings platform for training, serving, and managing representations at scale; streamlining feature engineering pipelines to reduce manual steps and deliver new signals quickly; developing automated continuous-learning systems that handle data refresh, retraining, evaluation, and drift monitoring with minimal manual effort; and scaling our training pipelines to support larger datasets, more complex architectures, and faster experimentation.

Across all of these efforts, you will work backward from applied ML projects that meaningfully improve accuracy—using those real-world scenarios to harden the platform capabilities that enable ML teams across Upstart to innovate with greater speed, reliability, and impact.

How You’ll Make an Impact

• Scale ML innovation by building tools, infrastructure, and workflows that dramatically improve the speed and reliability of model development.
• Work backward from modeling needs to design systems that directly unlock gains in accuracy, efficiency, and scientific productivity.
• Explore new algorithms and methodologies for our machine learning models and develop tooling to support them
• Improve the entire ML lifecycle—from data readiness and feature development through training, evaluation, serving, and monitoring.
• Automate and standardize operational workflows, enabling scientists to focus on high-leverage modeling and analysis rather than manual pipelines.
• Define the roadmap for our next generation ML Platform, balancing near-term impact with long-term architectural scalability.
• Collaborate cross-functionally with Data Engineering, ML Platform, Pricing, and other teams to build reliable, end-to-end ML systems.

Your work will multiply the effectiveness of every ML team at Upstart—accelerating innovation and advancing our mission to make credit more accurate, accessible, and fair.

This is a high influence role suited for those who enjoy combining science innovation, with cross functional collaboration and advisory. 

Minimum Qualifications

• 7+ years of hands-on experience in applied machine learning, with strong exposure to production-scale modeling efforts.
• Demonstrated expertise in end-to-end model development: data prep, feature engineering, training, evaluation, and deployment.
• Experience working in high-scale, ML-driven product environments—especially in fintech, pricing, or risk modeling.
• Proficiency in Python and core ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn, XGBoost).
• Ability to work autonomously and lead technical direction in ambiguous, high-impact domains.
• Experience collaborating with cross-functional teams including ML scientists, engineers, and product partners.
• Ability to bridge engineering and science teams, and influence technical strategy across disciplines.
• Numerically-savvy and smart with ability to operate at a fast pace
• Master’s degree or PhD in a quantitative discipline, or equivalent additional professional experience. 

Preferred Qualifications

• Practical experience optimizing ML workflows using CUDA/GPU acceleration.
• Background in feature store design, embedding architecture, or synthetic data generation for model training.
• Proven track record of improving model accuracy in production environments with measurable business outcomes.
• Familiarity with modern experimentation frameworks, hyperparameter tuning tools, and automated model selection techniques.

Open position in RADaR office locations, including Kansas City, MO, Columbia, MO, and St. Louis, MO; Hybrid work schedule: 3 days in the office, 2 days working from home

Visa sponsorship is not available for this position, now or in the future. Applicants must be legally authorized to work in the United States on a permanent basis without requiring employer sponsorship.

We're seeking a Data Scientist with exceptional statistical expertise to join our team. In this role, you'll work directly with advertising agencies and brands to analyze customer behavior patterns and advertising performance, developing sophisticated machine learning models that inform strategic marketing decisions.

Essential Duties and Responsibilities (Other duties may be assigned)

• Conduct deep statistical analysis of customer behavior data and advertising performance metrics across multiple channels and campaigns
• Design, develop, and deploy machine learning models to predict customer responses, optimize advertising spend, and identify high-value audience segments
• Perform advanced statistical modeling including regression analysis, hypothesis testing, time series analysis, and causal inference
• Build predictive models for customer lifetime value, churn prediction, attribution modeling, and campaign optimization
• Communicate complex analytical findings to both technical and non-technical stakeholders through compelling data visualizations and presentations
• Develop automated reporting solutions and dashboards that enable clients to monitor campaign performance in real-time
• Collaborate with cross-functional teams to ensure data quality and integrity across all analytics initiatives
• Stay current with emerging techniques in data science, machine learning, and marketing analytics

Qualifications - To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 3+ years of professional experience applying statistical methods and machine learning to business problems
• Strong foundation in statistical theory including probability, inference, experimental design, and multivariate analysis
• Demonstrated expertise in machine learning algorithms (e.g., random forests, gradient boosting, neural networks, clustering methods)
• Proficiency in Python or R for statistical analysis and machine learning, including libraries such as scikit-learn, pandas, NumPy, statsmodels
• Experience with SQL and working with large-scale databases
• Proven ability to design and analyze A/B tests and controlled experiments
• Track record of translating complex analytical insights into clear, actionable business recommendations
• Strong communication skills with the ability to present technical concepts to non-technical audiences

Preferred Qualifications:

• Experience working with advertising agencies, marketing teams, or in the ad tech industry
• Knowledge of digital advertising platforms (Google Ads, Facebook Ads, programmatic platforms)
• Familiarity with marketing attribution models and multi-touch attribution methods
• Experience with cloud computing platforms (AWS, GCP, or Azure)
• Knowledge of causal inference methods and their application to marketing effectiveness
• Experience with customer data platforms (CDPs) and marketing automation tools

Education

• Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Computer Science, Economics, or related quantitative field

Total Perks Package

• The chance to be a part of a growing company and the next success story
• Amazing opportunities for career development
• Recognition programs
• Employee referral bonus
• Hybrid work schedule; 3 days in the office, 2 days working from home
• Fun and collaborative work environment
• Casual dress code
• Insurance Coverage (medical, dental, vision, life, and disability)
• 401(k) retirement plan, with employer 4% match
• Work/life benefits, including mental health and wellbeing support
• Flexible Time Off Policy
• Paid holidays, including agency soft closing Christmas Eve-New Year's Day
• Paid leave options, including sick leave, medical leave for self and family, and parental leave

Open position in RADaR office locations, including Kansas City, MO, Columbia, MO, and St. Louis, MO; Hybrid work schedule: 3 days in the office, 2 days working from home

Visa sponsorship is not available for this position, now or in the future. Applicants must be legally authorized to work in the United States on a permanent basis without requiring employer sponsorship.

We're seeking a Data Scientist with exceptional statistical expertise to join our team. In this role, you'll work directly with advertising agencies and brands to analyze customer behavior patterns and advertising performance, developing sophisticated machine learning models that inform strategic marketing decisions.

Essential Duties and Responsibilities (Other duties may be assigned)

• Conduct deep statistical analysis of customer behavior data and advertising performance metrics across multiple channels and campaigns
• Design, develop, and deploy machine learning models to predict customer responses, optimize advertising spend, and identify high-value audience segments
• Perform advanced statistical modeling including regression analysis, hypothesis testing, time series analysis, and causal inference
• Build predictive models for customer lifetime value, churn prediction, attribution modeling, and campaign optimization
• Communicate complex analytical findings to both technical and non-technical stakeholders through compelling data visualizations and presentations
• Develop automated reporting solutions and dashboards that enable clients to monitor campaign performance in real-time
• Collaborate with cross-functional teams to ensure data quality and integrity across all analytics initiatives
• Stay current with emerging techniques in data science, machine learning, and marketing analytics

Qualifications - To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 3+ years of professional experience applying statistical methods and machine learning to business problems
• Strong foundation in statistical theory including probability, inference, experimental design, and multivariate analysis
• Demonstrated expertise in machine learning algorithms (e.g., random forests, gradient boosting, neural networks, clustering methods)
• Proficiency in Python or R for statistical analysis and machine learning, including libraries such as scikit-learn, pandas, NumPy, statsmodels
• Experience with SQL and working with large-scale databases
• Proven ability to design and analyze A/B tests and controlled experiments
• Track record of translating complex analytical insights into clear, actionable business recommendations
• Strong communication skills with the ability to present technical concepts to non-technical audiences

Preferred Qualifications:

• Experience working with advertising agencies, marketing teams, or in the ad tech industry
• Knowledge of digital advertising platforms (Google Ads, Facebook Ads, programmatic platforms)
• Familiarity with marketing attribution models and multi-touch attribution methods
• Experience with cloud computing platforms (AWS, GCP, or Azure)
• Knowledge of causal inference methods and their application to marketing effectiveness
• Experience with customer data platforms (CDPs) and marketing automation tools

Education

• Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Computer Science, Economics, or related quantitative field

Total Perks Package

• The chance to be a part of a growing company and the next success story
• Amazing opportunities for career development
• Recognition programs
• Employee referral bonus
• Hybrid work schedule; 3 days in the office, 2 days working from home
• Fun and collaborative work environment
• Casual dress code
• Insurance Coverage (medical, dental, vision, life, and disability)
• 401(k) retirement plan, with employer 4% match
• Work/life benefits, including mental health and wellbeing support
• Flexible Time Off Policy
• Paid holidays, including agency soft closing Christmas Eve-New Year's Day
• Paid leave options, including sick leave, medical leave for self and family, and parental leave

Open position in RADaR office locations, including Kansas City, MO, Columbia, MO, and St. Louis, MO; Hybrid work schedule: 3 days in the office, 2 days working from home

Visa sponsorship is not available for this position, now or in the future. Applicants must be legally authorized to work in the United States on a permanent basis without requiring employer sponsorship.

We're seeking a Data Scientist with exceptional statistical expertise to join our team. In this role, you'll work directly with advertising agencies and brands to analyze customer behavior patterns and advertising performance, developing sophisticated machine learning models that inform strategic marketing decisions.

Essential Duties and Responsibilities (Other duties may be assigned)

• Conduct deep statistical analysis of customer behavior data and advertising performance metrics across multiple channels and campaigns
• Design, develop, and deploy machine learning models to predict customer responses, optimize advertising spend, and identify high-value audience segments
• Perform advanced statistical modeling including regression analysis, hypothesis testing, time series analysis, and causal inference
• Build predictive models for customer lifetime value, churn prediction, attribution modeling, and campaign optimization
• Communicate complex analytical findings to both technical and non-technical stakeholders through compelling data visualizations and presentations
• Develop automated reporting solutions and dashboards that enable clients to monitor campaign performance in real-time
• Collaborate with cross-functional teams to ensure data quality and integrity across all analytics initiatives
• Stay current with emerging techniques in data science, machine learning, and marketing analytics

Qualifications - To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 3+ years of professional experience applying statistical methods and machine learning to business problems
• Strong foundation in statistical theory including probability, inference, experimental design, and multivariate analysis
• Demonstrated expertise in machine learning algorithms (e.g., random forests, gradient boosting, neural networks, clustering methods)
• Proficiency in Python or R for statistical analysis and machine learning, including libraries such as scikit-learn, pandas, NumPy, statsmodels
• Experience with SQL and working with large-scale databases
• Proven ability to design and analyze A/B tests and controlled experiments
• Track record of translating complex analytical insights into clear, actionable business recommendations
• Strong communication skills with the ability to present technical concepts to non-technical audiences

Preferred Qualifications:

• Experience working with advertising agencies, marketing teams, or in the ad tech industry
• Knowledge of digital advertising platforms (Google Ads, Facebook Ads, programmatic platforms)
• Familiarity with marketing attribution models and multi-touch attribution methods
• Experience with cloud computing platforms (AWS, GCP, or Azure)
• Knowledge of causal inference methods and their application to marketing effectiveness
• Experience with customer data platforms (CDPs) and marketing automation tools

Education

• Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Computer Science, Economics, or related quantitative field

Total Perks Package

• The chance to be a part of a growing company and the next success story
• Amazing opportunities for career development
• Recognition programs
• Employee referral bonus
• Hybrid work schedule; 3 days in the office, 2 days working from home
• Fun and collaborative work environment
• Casual dress code
• Insurance Coverage (medical, dental, vision, life, and disability)
• 401(k) retirement plan, with employer 4% match
• Work/life benefits, including mental health and wellbeing support
• Flexible Time Off Policy
• Paid holidays, including agency soft closing Christmas Eve-New Year's Day
• Paid leave options, including sick leave, medical leave for self and family, and parental leave

ABOUT THE TEAM

Anduril Labs is a multidisciplinary team of technologists, solution architects, engineers, and military subject matter experts. Its mission is to drive innovation across all Anduril business units and product lines by developing novel concepts and next-generation technologies that enhance Anduril’s competitive edge and give its customers a decisive technological advantage over its adversaries.

ABOUT THE JOB

We are looking for a talented full stack software engineer to join our growing team at Anduril Labs in Washington, DC. As a full stack software engineer in Anduril Labs, you will help bring innovative, next-generation concepts to life through proof-of-concept development and rapid prototyping using bleeding edge technologies.

The ideal candidate has exceptional software development and creative problem-solving skills, is a self-starter, and can quickly grasp complex concepts. As a full stack software engineer, you possess the skills to architect, develop, and deploy distributed applications and services, including both front-end and back-end components. You have experience with agile, end-to-end software development lifecycle and are comfortable developing and deploying code across Windows and Linux-based systems (including standalone bare-metal hardware, virtualized environments, and cloud-hosted platforms). Embedded software development experience is a plus. You are also proficient in integrating legacy code and systems, leveraging open-source technologies, and developing and utilizing APIs. Additionally, you have a solid understanding of AI/ML core concepts (e.g., feature extraction, supervised vs. unsupervised learning, regression, classification, clustering, deep learning neural networks, NLP, LLMs, SLMs, model fine-tuning, prompt engineering, RAG) and hands-on experience developing (Gen)AI-enhanced applications or services.

We also expect candidates to have familiarity with database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB) and experience with data modeling, data wrangling, analytics, and visualization. Since Anduril Labs supports all Anduril businesses and product lines, you will have the unique opportunity to work closely with multi-disciplinary engineering and product development teams across the entire company. This means you will get to directly contribute to the development of Anduril’s next-generation products and services. So if you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

WHAT YOU’LL DO

• Lead the development of prototypes to demonstrate advanced concepts in areas like autonomous and multi-agent systems, GenAI, advanced data analytics, quantum computing/sensing/networking/comms/machine learning, modeling, simulation, optimization, visualization, next-gen human-machine interfaces, heterogenous computing, and cybersecurity.
• Own the entire Software Development Lifecycle from inception through development, testing, deployment, and documentation for Anduril Labs-developed software prototypes.
• Interface and collaborate with other Anduril and customer engineering teams, and strategic partners.
• Support Anduril- and customer-funded R&D efforts.
• Participate in field experiments and technology demonstrations.

REQUIRED QUALIFICATIONS

• 3+ years of programming with Python, C++, Java, Rust, Go, or JavaScript/TypeScript.
• Proven software architecture and design skills.
• Ability to quickly understand and navigate complex systems and established codebases.
• AI/ML development using commercial and open-source AI frameworks, models, and tools (e.g., Jupyter Notebook, PyTorch, TensorFlow, Scikit-learn, OpenAI, Claude, Gemini, Llama, LangChain, YOLO, AWS Sagemaker, Bedrock, Azure AI, RAG).
• Web app development (e.g., React, Angular, or Vue).
• Cloud development (e.g., AWS, Azure, or GCP).
• Data modeling and wrangling.
• Networking basics (e.g., DNS, TCP/IP vs. UDP, socket communications, LDAP, Active Directory)
• Database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB).
• API development and integration (e.g., REST, GraphQL).
• Containerization technologies (e.g., Docker, Kubernetes).
• Software development on Linux and Windows.
• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.
• Experience with Git version control, build tools, and CI/CD pipelines.
• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.
• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.
• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance

PREFERRED QUALIFICATIONS

• BS in Computer Science, Engineering, or similar field.
• Distributed applications development (e.g., client/server, microservices, multi-agent solutions).
• High performance computing (HPC) and big data technologies (e.g., Apache Spark, Hadoop).
• Mobile app development (e.g., iOS or Android).
• Embedded software development experience.
• Willingness to travel up to approximately 10%

Location

Palo Alto, CA

Job Description

Rhombus’ Data Engineers are instrumental in designing and implementing data engineering activities on topical, mission-driven projects that inform our national security agenda. They analyze, build, and maintain our organization’s data infrastructure and processing systems. 

Additionally, our Data Engineers perform various code development and query needs for integration with new and existing applications, dashboards and machine learning pipelines. Our Data Engineers work cross functionally with other departments to meet business needs. They utilize their skills at all stages of the analytics pipeline to create results that drive business values and customer success.

Responsibilities:

• Develop code using various programming and scripting languages to automate data ingestion and improve data management processes.
• Architect data repositories, stand up data platforms and develop data pipelines for ingestion, transformation, and aggregation.
• Review existing architecture, data strategy, and improve processes for data governance, data quality, and metadata management.
• Extract and analyze raw data from multiple data sources via APIs, SQL Stored Procedures, or Python scripts.
• Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms.
• Collaborate with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced, agile environment.
• You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of scalable platforms for clients.
• Communicate project status and results to various levels of leadership.

Qualifications:

• At minimum Bachelor’s degree in Data Analytics, Computer Science, Computer Engineering, Information Systems/Sciences, or other relevant area (or equivalent experience) and at least 3 years of professional experience, or a Master’s degree with strong academic project experience and one year of work experience.  
• Experience with 1 or more programming and scripting languages, with a strong focus on Python, Pandas and Numpy. Other languages include: Shell, PERL, Java, C/C++/C#, Scala, etc.
• Experience with 1 or more of the following relational, noSQL and/or file based storage (e.g. MYSQL, MongoDB, SQL Server, Oracle, Postgres, Hbase, DynamoDB, etc.)
• Experience building and maintaining ETL data pipelines
• Experience with software development life cycle including testing, documenting, delivery and support
• Working knowledge of AWS/cloud technologies
• Experience using query optimization as well as data modeling techniques.
• Familiarity with machine learning frameworks (such as TensorFlow, Scikit-Learn, etc.)

Personal Qualities:

• Bias for action: Rhombus seeks ‘doers’ who will get things done with accuracy, speed and at scale.
• Ability to contextualize data as it relates to Rhombus’ vision. We want someone who can understand the “why” and “so what”, and not just the “how”. Our Data Engineers help us transmit the enthusiasm we have around the data work to the individuals doing that work.
• Must have strong problem-solving skills and demonstrated excellent oral and written communication skills.
• We’re seeking folks with strong intellectual curiosity and creativity, with an ability and willingness to learn new skills and apply novel solutions to problems.
• Comfort in a fast-paced start-up environment is crucial, with the ability to consistently revise your approach in response to new information, and to be flexible and adaptive.

Salary Range

• The estimated base salary range for this position is $110,000 to $180,000/year

Benefits 

• Full medical, dental, vision coverage for employee and dependents 
• 401k matching program 
• PTO and Holidays 
• Bonus and other incentive programs
• Access to mental health program
• Access to Flexible Spending Accounts for Health Care, Dependent and Commuter

About Rhombus 

Rhombus Power Inc. (Rhombus) is a startup located in the heart of Silicon Valley at Stanford Research Park in Palo Alto.  We use cutting-edge cross-disciplinary approaches to solve pressing Big Data and Sensing problems in security, energy, and healthcare. Our advisory board includes two Nobel Laureates and a Draper Prize winner. 

Rhombus compensates, motivates, and develops employees, who are trusted, empowered, and involved. Employees have clear roles and expectations – and their roles are flexible enough to move at the speed of innovation in order to meet and exceed client expectations. We have a unique culture of global purpose, rooted in the innovation and progress of Silicon Valley. 

Rhombus knows that diversity is a condition for success. We are committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action Employer. 

As a Sr. Solutions Architect at Databricks within the Field Engineering org, you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge, and can drive complex technology discussions that express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams, with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customers' needs, build valuable customer engagements, and report to the Field Engineering Manager.

The impact you will have:

• You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
• You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
• Become an expert in and promote Databricks-inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 8+ years in a customer-facing pre-sales or consulting role with expertise in at least one of the following technologies:
• Big data engineering (Ex: Spark, Hadoop, Kafka)
• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
• Fluent in SQL and database technology.
• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
• [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Travel to customers in your region up to 30% of the time.

Location: 439th CES/CER, 250 Patriot Avenue, Westover ARB, MA 01022 (Onsite)

Citizenship: US Citizen (MUST)

Security Clearance: Requires successful completion of NACI/SF85 (Public Trust) background investigation.

Position Overview:

The Support Specialist provides on-site, junior-level technical support to the 439th Civil Engineer Squadron (CES) at Westover ARB to help operate and sustain AI-enabled solutions in a secure DoD environment. Working under guidance from senior engineers and government stakeholders, the role supports day-to-day platform operations, basic data/model updates using established procedures, user support, and documentation for AI/ML-enabled capabilities (e.g., contract analysis, energy management, and snowfall recovery).

This position contributes to mission readiness by helping operationalize and improve critical AI-driven platforms for military engineering, utilities, contracting, and emergency response.

Key Responsibilities:

• AI/ML support: Run established training/evaluation scripts and assist with basic model validation, tuning experiments, and periodic updates under supervision.
• Deployment & integration support: Assist with deployments in secure, on-site/air-gapped environments by following checklists and runbooks; support integration testing and coordinate tickets with DoD IT/cyber teams.
• Documentation: Update and maintain technical notes, user guides, and training materials using provided templates and standards.
• Training support: Assist with recurring user training and help translate technical workflows for non-technical users; capture feedback and improvement requests.
• Security: Follow DoD cybersecurity requirements; protect CUI/FCI; comply with privacy and confidentiality rules.
• Sustainment: Perform basic monitoring and health checks; execute approved patches/updates using runbooks; troubleshoot common issues and escalate complex problems.
• Reporting: Support labor-hour reporting and contract deliverables on Government timelines.
• Coordination: Log, track, and triage support tickets/incidents; communicate status updates; coordinate with the Resources Flight Chief and technical leads to resolve issues.

Required Qualifications:

• Education: Bachelor’s degree in computer science, engineering, data science, or related field.
• Experience: Minimum of 2 years’ direct hands-on experience or commensurate education in artificial intelligence, machine learning, data science, or a related field within secure DoD or comparable environments.
• Technical Skills: Working knowledge of Python; basic Linux command line; Git/version control; ability to run and troubleshoot scripts; familiarity with at least one ML library (e.g., scikit-learn or PyTorch/TensorFlow) and basic data handling (CSV/SQL fundamentals).
• Security & compliance: Ability to follow secure handling procedures for CUI/FCI and comply with DoD/site security requirements; willingness to complete required security and privacy training.
• Communication: Clear verbal and written communication for technical and non-technical audiences; able to draft documentation and provide status updates with guidance.
• Professionalism: Present a professional appearance; display contractor identification badges at all times; adhere to all base regulations and government conduct policies.

Additional Requirements:

• U.S. citizenship; eligible for base access.
• Occasional travel to other AFRC locations, as authorized.
• Compliance with privacy, safety, and physical/environmental security rules.
• Maintain service continuity and follow contract staffing constraints.
• Maintain personally issued computing equipment per contract terms.

Preferred Qualifications:

• Prior support for .mil/.gov AI, data, or software solutions (internships/projects count).
• Familiarity with DoD acquisition/contracting and compliance processes.
• Familiarity with containers (Docker) and/or basic CI/CD concepts; interest in automation/scripting to improve repeatable support tasks.

About the Staff Machine Learning Engineer at Headspace:

The AI & Machine Learning group at Headspace is a dynamic and innovative group whose mission is to improve the experiences of our members and clinicians through the mindful application of AI. Our group builds conversational AI systems including Ebb, as well as search, recommendation & personalization systems that power the Headspace experience. The Staff ML Engineer for Personalization will be part of the team developing and delivering the holistic system to enable the personalization of the Headspace experience, including content recommendation, personalized nudges & notifications, and a tailored conversational AI experience with Ebb. You’ll have the opportunity to lead the vision, alignment, development, deployment, and adoption of these solutions, helping to realize Headspace’s mission to improve the health and happiness of the world.

What you will do:

• Technical Leadership: Lead the development of recommender systems for Headspace meditation & mindfulness content as well as other backend services that enable a personalized member experience including search, a user knowledge graph, and conversational AI memory. This will involve developing and deploying complex, scalable AI models and applications. Drive impactful ML technology initiatives that will shape the delivery of and access to mental healthcare. Serve as a go-to expert and mentor, exemplifying excellence in AI/ML engineering and inspiring others to pursue technical career growth.
• Shape Personalization Architecture: Contribute to the design, development, and evolution of our AI systems, taking it from high-level vision to robust implementation, enabling production-ready AI capabilities.
• Collaborative Problem-Solving: Partner with our team of software engineers,ML engineers, and MLOps engineers, and our Product & Clinical leads to build high quality features that improve members’ lives.

What you will bring:

Required Skills:

• Bachelor of Science degree or higher in Computer Science, Statistics, Mathematics or a related field OR equivalent experience
• 5+ years of ML engineering experience in an academic or professional setting, programming in Python
• 5+ years of experience with any of the following fundamental technologies: vector search, embedding models, recommender systems, supervised, unsupervised machine learning, deep learning, reinforcement learning, LLM orchestration, RAG systems.
• 3+ years of experience with modern NLP tools and machine learning libraries (scikit-learn, PyTorch, TensorFlow, spaCy)
• Experience with unit, integration, and end-to-end testing, version control
• Strong problem solving and communication skills and ability to influence across internal organizations
• Mentorship of junior engineers and contribution to DEIB initiatives

Preferred Skills:

• Master’s degree in relevant field or equivalent experience
• Professional experience with clinical and/or healthcare applications of machine learning
• Familiarity with current ML literature
• Experience with implementation of robust and highly scalable services
• Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM

Location: We are currently hiring this role remotely. Candidates must permanently reside in the US full-time.

For candidates with a primary residence in the greater SF area, this role will follow our hybrid model. You’ll work 3 days per week from our office, allowing for impactful in-office collaboration and connection, while enjoying the flexibility of remote work for the rest of the week. Your recruiter will share more details about our hybrid model. 

Pay & Benefits:

The anticipated new hire base salary range for this full-time position is $140,400-$200,000 + equity + benefits. 

Our salary ranges are based on the job, level, and location, and reflect the lowest to highest geographic markets where we are hiring for this role within the United States. Within this range, individual compensation is determined by a candidate’s location as well as a range of factors including but not limited to: unique relevant experience, job-related skills, and education or training. 
Your recruiter will provide more details on the specific salary range for your location during the hiring process.

At Headspace, base salary is but one component of our Total Rewards package. We’re proud of our robust package inclusive of: base salary, stock awards, comprehensive healthcare coverage, monthly wellness stipend, retirement savings match, lifetime Headspace membership, generous parental leave, and more. Additional details about our Total Rewards package will be provided during the recruitment process. 

About Headspace

Headspace exists to provide every person access to lifelong mental health support. We combine evidence-based content, clinical care, and innovative technology to help millions of members around the world get support that’s effective, personalized, and truly accessible whenever and wherever they need it.

At Headspace, our values aren’t just what we believe, they’re how we work, grow, and make an impact together. We live them daily: Make the Mission Matter, Iterate to Great, Own the Outcome, and Connect with Courage. These values shape our decisions, guide our collaborations, and define our culture. They’re our shared commitment to building a more connected, human-centered team—one that’s redefining how mental health care supports people today and for generations to come.

Why You’ll Love Working Here:

A mission that matters—with impact you can see and feel

A culture that’s collaborative, inclusive, and grounded in our values

The chance to shape what mental health care looks like next

Competitive pay and benefits that support your whole self

How we feel about Diversity, Equity, Inclusion and Belonging:

Headspace is committed to bringing together humans from different backgrounds and perspectives, providing employees with a safe and welcoming work environment free of discrimination and harassment. We strive to create a diverse & inclusive environment where everyone can thrive, feel a sense of belonging, and do impactful work together. 

As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, family or parental status, disability*, age, veteran status, or any other status protected by the laws or regulations in the locations where we operate. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our workplace. 

*Applicants with disabilities may be entitled to reasonable accommodation under the terms of the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Headspace. Please inform our Talent team by filling out this form if you need any assistance completing any forms or to otherwise participate in the application or interview process.

Headspace participates in the E-Verify Program.

Privacy Statement

All member records are protected according to our Privacy Policy. Further, while employees of Headspace (formerly Ginger) cannot access Headspace products/services, they will be offered benefits according to the company's benefit plan. To ensure we are adhering to best practice and ethical guidelines in the field of mental health, we take care to avoid dual relationships. A dual relationship occurs when a mental health care provider has a second, significantly different relationship with their client in addition to the traditional client-therapist relationship—including, for example, a managerial relationship.  

As such, Headspace requests that individuals who have received coaching or clinical services at Headspace wait until their care with Headspace is complete before applying for a position. If someone with a Headspace account is hired for a position, please note their account will be deactivated and they will not be able to use Headspace services for the duration of their employment. 

Further, if Headspace cannot find a role that fails to resolve an ethical issue associated with a dual relationship, Headspace may need to take steps to ensure ethical obligations are being adhered to, including a delayed start date or a potential leave of absence. Such steps would be taken to protect both the former member, as well as any relevant individuals from their care team, from impairment, risk of exploitation, or harm.

For how how we will use the personal information you provide as part of the application process, please see: https://www.headspace.com/applicant-notice

About the Principal Machine Learning Engineer at Headspace:

Machine Learning at Headspace is a dynamic and innovative group whose mission is to improve the experiences of our members and clinicians through the mindful application of Machine Learning. These applications include building conversational AI systems, healthcare assistance tools, and recommendation and personalization systems. In this team, you’ll be tasked with owning and delivering cutting edge language-based ML applications that will power the core features of Headspace. You’ll have the opportunity to lead the vision, alignment, development, deployment, and adoption of these solutions, helping to bring Headspace to the forefront of AI and to realize its mission to improve health and happiness of the world.

What you will do:

• Technical Leadership: Lead the development of complex, scalable AI models and applications from inception to production. Drive impactful ML technology initiatives that will shape the delivery of and access to mental healthcare. Serve as a go-to expert and mentor, exemplifying excellence in AI/ML engineering and inspiring others to pursue technical career growth.
• Shape ML Platform Architecture: Drive the design, development, and evolution of our internal ML platform, taking it from high-level vision to robust implementation.
• Collaborative Problem-Solving: Partner with cross-functional teams to align technical decisions with organizational goals, ensuring cohesive and impactful solutions.

What you will bring:

Required Skills:

• Master’s of Science degree or higher in Computer Science, Statistics, Mathematics or a related field OR equivalent experience
• 8+ years of ML engineering experience in an academic or professional setting, programming in Python
• 8+ years of experience with any of the following fundamental technologies: vector search, embedding models, recommender systems, supervised, unsupervised machine learning, deep learning, reinforcement learning, LLM orchestration, RAG systems.
• 5+ years of experience with modern NLP tools and machine learning libraries (scikit-learn, PyTorch, TensorFlow, spaCy)
• Experience with unit, integration, and end-to-end testing, version control
• Strong problem solving and communication skills and ability to influence across internal organizations
• Mentorship of junior engineers and contribution to DEIB initiatives

Preferred Skills:

• PhD in relevant field or equivalent experience
• Professional experience with clinical and/or healthcare applications of machine learning
• Familiarity with current ML literature including optimization methods and agent-based models
• Experience with implementation of robust and highly scalable services
• Experience with AWS, including SageMaker, Lambda, S3, DynamoDB, IAM

Location: We are currently hiring this role Remotely. If located in San Francisco then it will be hybrid (3 days a week). Candidates must permanently reside in the US full-time.

For candidates with a primary residence in the greater SF area, this role will follow our hybrid model. You’ll work 3 days per week from our office, allowing for impactful in-office collaboration and connection, while enjoying the flexibility of remote work for the rest of the week. Your recruiter will share more details about our hybrid model. 

Pay & Benefits:

The anticipated new hire base salary range for this full-time position is $162,000-$250,000 + equity + benefits. 

Our salary ranges are based on the job, level, and location, and reflect the lowest to highest geographic markets where we are hiring for this role within the United States. Within this range, individual compensation is determined by a candidate’s location as well as a range of factors including but not limited to: unique relevant experience, job-related skills, and education or training. 
Your recruiter will provide more details on the specific salary range for your location during the hiring process.

At Headspace, base salary is but one component of our Total Rewards package. We’re proud of our robust package inclusive of: base salary, stock awards, comprehensive healthcare coverage, monthly wellness stipend, retirement savings match, lifetime Headspace membership, generous parental leave, and more. Additional details about our Total Rewards package will be provided during the recruitment process. 

About Headspace

Headspace exists to provide every person access to lifelong mental health support. We combine evidence-based content, clinical care, and innovative technology to help millions of members around the world get support that’s effective, personalized, and truly accessible whenever and wherever they need it.

At Headspace, our values aren’t just what we believe, they’re how we work, grow, and make an impact together. We live them daily: Make the Mission Matter, Iterate to Great, Own the Outcome, and Connect with Courage. These values shape our decisions, guide our collaborations, and define our culture. They’re our shared commitment to building a more connected, human-centered team—one that’s redefining how mental health care supports people today and for generations to come.

Why You’ll Love Working Here:

A mission that matters—with impact you can see and feel

A culture that’s collaborative, inclusive, and grounded in our values

The chance to shape what mental health care looks like next

Competitive pay and benefits that support your whole self

How we feel about Diversity, Equity, Inclusion and Belonging:

Headspace is committed to bringing together humans from different backgrounds and perspectives, providing employees with a safe and welcoming work environment free of discrimination and harassment. We strive to create a diverse & inclusive environment where everyone can thrive, feel a sense of belonging, and do impactful work together. 

As an equal opportunity employer, we prohibit any unlawful discrimination against a job applicant on the basis of their race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, family or parental status, disability*, age, veteran status, or any other status protected by the laws or regulations in the locations where we operate. We respect the laws enforced by the EEOC and are dedicated to going above and beyond in fostering diversity across our workplace. 

*Applicants with disabilities may be entitled to reasonable accommodation under the terms of the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Headspace. Please inform our Talent team by filling out this form if you need any assistance completing any forms or to otherwise participate in the application or interview process.

Headspace participates in the E-Verify Program.

Privacy Statement

All member records are protected according to our Privacy Policy. Further, while employees of Headspace (formerly Ginger) cannot access Headspace products/services, they will be offered benefits according to the company's benefit plan. To ensure we are adhering to best practice and ethical guidelines in the field of mental health, we take care to avoid dual relationships. A dual relationship occurs when a mental health care provider has a second, significantly different relationship with their client in addition to the traditional client-therapist relationship—including, for example, a managerial relationship.  

As such, Headspace requests that individuals who have received coaching or clinical services at Headspace wait until their care with Headspace is complete before applying for a position. If someone with a Headspace account is hired for a position, please note their account will be deactivated and they will not be able to use Headspace services for the duration of their employment. 

Further, if Headspace cannot find a role that fails to resolve an ethical issue associated with a dual relationship, Headspace may need to take steps to ensure ethical obligations are being adhered to, including a delayed start date or a potential leave of absence. Such steps would be taken to protect both the former member, as well as any relevant individuals from their care team, from impairment, risk of exploitation, or harm.

For how how we will use the personal information you provide as part of the application process, please see: https://www.headspace.com/applicant-notice

THE COMPANY:

Juul Labs's mission is to transition the world’s billion adult smokers away from combustible cigarettes, eliminate their use, and combat underage usage of our products. We have the opportunity to address one of the world’s most intractable challenges through a commitment to exceptional quality, research, design, and innovation. Backed by leading technology investors, we are committed to the same excellence when it comes to hiring great talent.

We are a diverse team that is united by this common purpose and we are hiring the world’s best engineers, scientists, designers, product managers, operations experts, and customer service and business professionals. If the opportunity to build your career is compelling, read on for more details.

ROLE AND RESPONSIBILITIES:

The Mechatronics Engineer is a hands-on role that will be responsible for designing new products that are innovative, cost efficient, reliable, and ship on schedule. This role will drive the validation of concepts via early analysis, prototyping and testing, and work with cross-functional teams to ensure that product requirements are managed to achieve optimal experiences for our customers. In addition, the Mechatronics Engineer will work closely with internal and external partners to technically define designs and ensure that all product and project requirements are met. You will troubleshoot and make improvements to existing products and new products as well as test instrumentation. You will  work closely with other members of the engineering staff to create optimal solutions to a myriad of product related topics such as but not limited to mechanical design, thermal, and data analytics. You will be comfortable sketching and prototyping new ideas and be familiar with engineering best practices, concepts and procedures. We are looking for someone who is flexible and can respond quickly, energetically, and enthusiastically to changes. The person in this role should be a strong communicator who is able to lead effectively and work effectively with peers and management alike in a high-paced global environment. 

• Experienced with embedded control systems and adept at deriving meaningful insights through data analytics to drive improvements in existing algorithms.
• Leverage existing tools, systems, and/or processes for data collection and analysis.
• Takes initiative and ownership of high level work. Negotiates and drives alignment with product architects, managers, and other key stakeholders across multiple disciplines.
• Design, implement, and drive to completion complex system DoEs spanning several engineering disciplines including EE, ME, FW, and SW. 

PERSONAL AND PROFESSIONAL QUALIFICATIONS: 

• Min 2 years working experience in Python and C++ software development, including system design, data structures & algorithms.
• Experienced with Python and Jupyter Notebooks; specifically, numpy, pandas, scipy, and sklearn.
• Prototyping background: Have a maker mentality that allows you to prototype quickly while also producing robust systems that sustain through heavy use and have well-documented construction and troubleshooting guidelines
• 3-5 years of relevant engineering experience in one or more of the following areas: product design, new product release, test engineering.
• Conduct rapid feasibility studies to design for mechanical, fluidic, and thermal robustness.
• Experienced in developing and testing both software applications and mechanical systems, ensuring they work together.
• Oversee internal and external prototyping.
• Work directly with our CM or prototyping partners in support of system assembly build activities.
• Expertise in one (or more of) the areas of: Statistical Analysis, Design of Experiments, Thermal Design, etc.
• Expertise in 3D MCAD, Solidworks preferred.

EDUCATION 

The ideal candidate will possess a Bachelor's degree or higher in Mechatronics, Mechanical Engineering, or a related field

JUUL LABS PERKS & BENEFITS:

• A place to grow your career. We’ll help you set big goals - and exceed them
• People. Work with talented, committed and supportive teammates
• Equity and performance bonuses. Every employee is a stakeholder in our success
• Cell phone subsidy, commuter benefits and discounts on JUUL products
• Excellent medical, dental and vision, disability, and life insurance, plus family support, wellness, legal, and employee assistance program benefits
• 401(k) plan with company matching
• Plus biannual discretionary performance bonuses

Juul Labs is proud to be an equal opportunity employer and is committed to creating a diverse and inclusive work environment for all employees and job applicants, without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. We will consider for employment qualified applicants with arrest and conviction records, pursuant to the San Francisco Fair Chance Ordinance. Juul Labs also complies with the employment eligibility verification requirements of the Immigration and Nationality Act. All applicants must have authorization to work for Juul Labs in the US.

Make your impact within a rapidly growing Fintech Company

Join BILL's AI Product Engineering team and help shape the future of intelligent financial automation. As a Senior Machine Learning Engineer, you'll play a pivotal role in designing, building, and deploying machine learning solutions that power BILL's next-generation products. This is an opportunity to work in a collaborative, high-impact environment where your expertise will directly influence the company's growth and the experience of millions of users.

Responsibilities:

• Design, develop, and deploy robust machine learning models to solve real-world business challenges in the fintech domain
• Collaborate cross-functionally with product managers, engineers, and data scientists to translate business requirements into scalable ML solutions
• Analyze complex datasets, identify patterns, and extract actionable insights to drive product innovation
• Evaluate, optimize, and monitor model performance in production, ensuring reliability and accuracy over time
• Contribute to the development and improvement of AI workflows, agentic evaluation and best practices within the team
• Document methodologies, experiments, and results to ensure knowledge sharing and reproducibility
• Mentor junior team members and share technical expertise to elevate team capabilities

We’d love to chat if you have:

• Proven experience building and deploying machine learning models in production environments
• Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Previous experience with OCR extraction and NLP methodologies
• Knowledge of AI agents and strong experience with LLMs
• Ability to analyze and interpret large, complex datasets using statistical and data analysis techniques
• Excellent communication and collaboration skills, with a track record of working effectively in cross-functional teams
• A problem-solving mindset and a passion for continuous learning and innovation

Visa Sponsorship:  Please note that this position is eligible for visa sponsorship.

#LI

Make your impact within a rapidly growing Fintech Company

Join BILL's AI Product Engineering team and help shape the future of intelligent financial automation. As a Senior Machine Learning Engineer, you'll play a pivotal role in designing, building, and deploying machine learning solutions that power BILL's next-generation products. This is an opportunity to work in a collaborative, high-impact environment where your expertise will directly influence the company's growth and the experience of millions of users.

Responsibilities:

• Design, develop, and deploy robust machine learning models to solve real-world business challenges in the fintech domain
• Collaborate cross-functionally with product managers, engineers, and data scientists to translate business requirements into scalable ML solutions
• Analyze complex datasets, identify patterns, and extract actionable insights to drive product innovation
• Evaluate, optimize, and monitor model performance in production, ensuring reliability and accuracy over time
• Contribute to the development and improvement of AI workflows, agentic evaluation and best practices within the team
• Document methodologies, experiments, and results to ensure knowledge sharing and reproducibility
• Mentor junior team members and share technical expertise to elevate team capabilities

We’d love to chat if you have:

• Proven experience building and deploying machine learning models in production environments
• Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Previous experience with OCR extraction and NLP methodologies
• Knowledge of AI agents and strong experience with LLMs
• Ability to analyze and interpret large, complex datasets using statistical and data analysis techniques
• Excellent communication and collaboration skills, with a track record of working effectively in cross-functional teams
• A problem-solving mindset and a passion for continuous learning and innovation

Visa Sponsorship:  Please note that this position is eligible for visa sponsorship. 

#LI

Polar Operations LLC (dba IMC Markets) has multiple openings for Python Software Engineer (REQ#4461661101) in Chicago, IL and Brooklyn, NY.

Your Core Responsibilities

• Implement software features and components for IMC's trading systems (25%).
• Design software solutions independently and make architectural decisions (10%).
• Debug and fix software issues in trading systems (5%).
• Identify complex multi-component issues, perform root cause analysis, and implement preventative solutions (5%).
• Ensure code quality and system reliability through comprehensive automated testing (10%).
• Contribute to the automated testing framework, own critical trading system components, and ensure reliability, performance, and scalability across regions (5%).
• Participate in code reviews (10%).
• Monitor system performance and trading operations (5%).
• Collaborate with traders and other teams to understand requirements and deliver solutions (10%).
• Participate in planning, estimate complexity of tasks, and help balance technical debt with feature development (5%).
• Mentor and guide junior developers and interns, helping them understand IMC's systems and development practices (10%).

Partial telecommuting permitted. Multiple positions available. Requisition #: 4461661101

Your Skills and Experience

This position requires a Bachelor’s degree, or foreign equivalent, in Computer science, Computer Engineering, or a similarly quantitative and technical field and one (1) year of experience in the job offered or a related occupation.

Must have at least one (1) year of experience in each of the following skill(s):

• Applying analytical and engineering techniques to solve complex problems programmatically;
• Programming with Python;
• Developing and implementing algorithms and data structures;
• Software development lifecycle and best practices;
• Designing and developing software applications in a collaborative, cross-functional environment;
• Experience with DevOps, databases, big data, or frontend frameworks;
• Experience with Docker, Kubernetes, and Linux environments;
• Experience working with financial data;
• Foundational knowledge of quantitative trading concepts and equity/index options;
• Exposure to web/API frameworks such as FastAPI and React;
• Experience with automated testing and CI/CD pipelines;
• Experience collaborating with trading desks and developing software for use in a quantitative trading environment;
• Experience with the following tools: Team City, JIRA ticket management, Gerrit code review tool, GitLab, uv, Gitlab CI, py-spy, memray, and Python Packaging; and
• Experience with the following libraries: Pandas, Polars, NumPy, Tensorflow, Scikit, scikit-learn, cvxpy, and Pytest.

#LI-DNI

What Impact You’ll Have

GRVTY’s team provides tactical data engineering solutions. We embed skilled Data Engineers, Data Scientists, and ETL Developers directly into intelligence analyst groups to be their go-to data wranglers. We develop new tools, code, and services to execute data engineering activities. Our engineers work to collect, process, and feed analytic tools, turning data into intelligence in response to immediate mission needs, with direct impact on real world situations. You will see your work used here on a daily basis, and you'll have the opportunity to support a variety of Sponsor mission organizations and mission partner organizations.
This is a time of development and growth on the program, with an increasing number of missions being supported. The work is high impact and important, and the customer moves quickly. The environment is fast-paced, flexible, and open to innovation - you'll have more latitude here in choosing how to achieve results than on many other projects. The customer cares more about what you can do as opposed to your years of
experience, and work hours are typically quite flexible - roll up your sleeves, get things done, and no one cares much about the specific hours that you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr, Kibana, neo4J, MariaDB, Postgres, Docker, Puppet, and many others. Work on this program takes place in McLean, VA and in various field offices throughout Northern VA (we cannot support remote work) and requires a TS/SCI + Polygraph clearance (acceptable to this customer).

What You’ll Be Owning

GRVTY is seeking a Network Engineer with a TS/SCI + Poly clearance (applicable to this customer) to join one of our top projects in Chantilly, VA. Seeking an experienced Network Engineer that will be responsible for managing and maintaining the organization's complex and secure network infrastructure. Must have at least 5 years of experience with configuring Cisco IOS and/or Cisco NX-OS in a datacenter environment including experience configuring VLANs, Routing, and security settings.  Experience in top of rack configurations and storage area network configuration is preferred but not required. Has experience with Cisco implementations who can optimize network processing and operations. Ability to work independently as well as be a part of an agile team to transform the client's hybrid cloud platform.

What You Must Have

• Active TS/SCI with Polygraph Clearance
• Minimum of 5 years of experience with:
• Configuring Cisco IOS and/or Cisco NX-OS in a data center environment
• Experience with VLANs, routing and security settings
• Cisco implementations, network processing and operations

Founded in Silicon Valley in 2009 by Marc Andreessen and Ben Horowitz, Andreessen Horowitz (aka a16z) is a venture capital firm that backs bold entrepreneurs building the future through technology. We are stage agnostic. We invest in seed to venture to growth-stage technology companies, across AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and companies building toward American dynamism. a16z has $100B+ under management across multiple funds.

We’ve established a team that is defined by respect for the entrepreneur and the company-building process; we know what it’s like to be in the founder’s shoes. We’ve invested in companies like Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. Our team is at the forefront of new technology, helping founders and their companies impact and change the world.

The Role

You will join a team of highly autonomous, senior ICs developing both software capabilities for the firm’s investing and operating functions, and external-facing products for the firm’s partners, portfolio, and investors. This role specifically involves leading the technical strategy, architecture, and implementation of machine learning systems that power the firm’s internal and external-facing applications. You will be responsible for the entire model lifecycle, from feature engineering and training to large-scale, low-latency serving and robust MLOps infrastructure.

The Applied Software Group operates in the mode of an internal startup. We own an exceptionally tight feedback loop and take on requests from all corners of the firm. This is a high-visibility role that requires a clear architectural vision, strong software engineering fundamentals, exacting communication skills, and the ability to engage and educate our firm on the technology we are developing and shipping.

This role requires an in-office presence 2-3 days a week in our San Francisco, CA office.

To join our team, you should be excited to:

• Architect, build, and maintain scalable and reliable ML production pipelines (data, training, and inference)
• Collaborate with the Applied Software Group (ASG) team to integrate ML models into user-facing products serving the investing partnership and our operating teams
• Set and evolve MLOps standards for the team, including producibility, automated testing, CI/CD, observability, and model governance across the firm.
• Research and lead the implementation of model serving strategies (e.g., real-time APIs, batch processing) to meet strict latency and throughput requirements
• Drive the technical roadmap for core ML infrastructure, influencing platform choices and building cloud-native systems primarily on GCP.
• Operate with high autonomy, owning outcomes end-to-end, proactively identifying gaps, and raising the technical bar for the team.
• Set a high standard for code quality and system design, producing clear, principled, and extensible solutions that scale with the firm.
• Bring positive energy in every interaction with the team and foster inclusive collaboration
• Learn the inner workings of VC and work closely with the investing partnership

Minimum Qualifications

• 2+ years of professional experience as a Machine Learning Engineer or similar role.
• Strong mathematical intuition and problem-solving skills
• Expertise in Python and its statistical modeling ecosystem (e.g. NumPy, scikit-learn, etc.)
• Solid experience with major ML frameworks like PyTorch, TensorFlow, or JAX
• Proven experience deploying and managing ML models in a production environment using tools like Kubeflow, MLflow, Airflow, or TFX
• Strong understanding of containerization technologies (e.g., Docker, Kubernetes/GKE) as applied to ML serving
• Familiarity with cloud computing environments (preferably GCP), including data storage and compute services
• Low ego, high empathy, and the capacity to collaborate effectively with diverse teams

The anticipated salary range for this role is between $341,000 - $422,000, actual starting pay may vary based on a range of factors which can include experience, skills, and scope.

This role is eligible to participate in the a16z carry program and various discretionary bonus programs as well as benefit and perquisite plans including health, dental, vision, disability, life insurance, 401K plan, vacation, and sick leave.

The Community You Will Join:

At Airbnb, we believe technology has the power to bring people together — and our engineers are the ones building it. Our Engineering org is a diverse, fast-moving group of teams working across Payments, Trust, Marketing, Relevance & Personalization, and more. Together, we're tackling some of the hardest problems in tech: search relevance at global scale, fraud prevention, seamless payments, and fueling growth — all while delivering a product experience that feels effortless and beautiful. We're also at the forefront of integrating AI and machine learning into our products — from personalized search experiences to intelligent trust and safety systems — and we're looking for curious engineers who are excited to grow alongside this technology.

If you're energized by engineering that creates real-world human connection — and by the idea that your code will be experienced by millions of people around the world — you'll feel right at home here.

The Difference You Will Make:

As a Software Engineer (New Grad) at Airbnb, you’ll play a vital role in building, supporting, and refining the products and systems that make Airbnb’s mission possible. Your work will directly contribute to high-quality, reliable experiences for our global community—whether you’re fixing bugs, launching well-defined features, or enhancing existing components. You'll also have the opportunity to contribute to AI-powered features, applying foundational knowledge of machine learning concepts and modern AI tools to build smarter, more personalized experiences for our hosts and guests. By clearly communicating challenges and collaborating with teammates across functions, you’ll help drive projects forward with transparency and trust.

You’ll foster a sense of belonging by actively seeking feedback, sharing your own learnings, and supporting the onboarding of new team members. You’ll help uphold Airbnb’s commitment to excellence by following best practices, delivering tasks autonomously, and continually improving your technical skills. Your curiosity, empathy, and commitment to candid communication will empower you to make a meaningful impact—on projects, teammates, and Airbnb’s inclusive culture.

A Typical Day: 

• Attend team syncs to discuss priorities, share progress, and surface any blockers with transparency.
• Dive into coding—fixing bugs, developing features, or refining APIs and components—while applying best practices for code quality, error handling, and testability. Leverage AI-assisted development tools (e.g., Claude Code or similar) to accelerate your workflow and improve code quality.
• Participate in design or code reviews, ask clarifying questions, and apply feedback to improve your work. Work closely with cross-functional partners like product managers and designers to ensure your tasks align clearly with broader goals.
• Dedicate time to expanding your technical knowledge through documentation, mentorship, or internal knowledge-sharing sessions. This includes staying current on AI/ML developments relevant to your team's domain — whether that's recommendation systems, natural language understanding, or AI safety practices. Seek guidance from managers or tech leads when tackling unfamiliar problems.
• Contribute to team activities, such as onboarding new hires (e.g., being an onboarding buddy), sharing observations from the hiring process, or joining in cultural events focused on diversity, inclusion, and innovation.
• Share updates on your progress and next steps, highlighting challenges or learnings. 

Your Expertise:

This role is designed for recent graduates (Bachelor's or Master's) with less than 1 year of full-time professional experience who are ready to grow fast and make an impact.

• Strong foundation in Computer Science fundamentals — data structures, algorithms, design patterns, and systems thinking
• Proficiency in one or more of: Java, Scala, Ruby, Ruby on Rails, C++, SQL, HTML/CSS, JavaScript, Objective-C, Swift (iOS), or Kotlin (Android)
• Foundational awareness of AI/ML concepts — such as supervised learning, model evaluation, or working with APIs backed by large language models (LLMs) — gained through coursework, personal projects, or internships
• Familiarity with Python and common AI/ML libraries (e.g., NumPy, scikit-learn, or PyTorch) is a plus, as is experience integrating cloud-based AI services or LLM APIs
• An understanding of responsible AI principles — including fairness, privacy, and safety — and a curiosity about how these apply to real-world product development
• Bonus points for leadership experience, community involvement, or teaching/mentoring — we love engineers who invest in others

Your Location:

Preference for candidates based in San Francisco, California or Seattle, Washington with the ability to commute to the office three days per week. Additional in-person attendance for team meetings or offsites may be required as needed. Domestic Relocation support will be provided for candidates open to relocating.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. 

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

CSQ127R67

PLEASE NOTE:
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our federal government customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems.
• Own production rollouts of consumer and internally facing GenAI applications.
• Serve as a trusted technical advisor to customers across a variety of domains.
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally.
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap.

What we look for:

• Experience working with U.S. federal civilian, state, or local agencies. 
• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy.
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations.
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.).
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike.
• Passion for collaboration, life-long learning, and driving business value through AI.
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets.

The role:

We're looking for a Senior Manager, Data Science/ML who will drive CookUnity's next phase of product innovation through forward-looking data science capabilities. This role goes beyond traditional analytics—you'll be responsible for building the ML and experimentation foundation that enables personalized, intelligent product experiences at scale.

As Senior Manager, you'll own the strategic vision for how data science shapes our product roadmap. You'll build and lead a team focused on predictive modeling, personalization, experimentation frameworks, and emerging ML capabilities that directly impact customer engagement, retention, and lifetime value. This is a high-impact role for someone who thinks strategically about the future of product science while remaining hands-on in driving technical execution.

Responsibilities:

Strategic Vision & Product Partnership

• Define and execute the product data science strategy, identifying opportunities where ML and predictive analytics can unlock step-change improvements in customer experience and business outcomes
• Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap with data-driven insights and forward-looking ML capabilities
• Act as a thought leader on emerging data science techniques (personalization, recommendation systems, causal inference, generative AI) and their application to product problems
• Translate complex product challenges into clear data science problems with measurable success criteria
• Own the end-to-end ML lifecycle for product use cases: problem framing, feature development, model training, deployment, monitoring, and iteration
• Partner with the Growth Data Science & Analytics team to align experimentation, measurement, and modeling efforts into a cohesive end-to-end data science ecosystem.

Team Leadership & Development

• Build, mentor, and scale a high-performing product data science team capable of delivering both strategic insights and production ML systems
• Foster a culture of innovation, experimentation, and continuous learning within the data science organization
• Create career development pathways that attract and retain top data science talent
• Collaborate with Analytics Engineering to ensure seamless model deployment and monitoring

Advanced Analytics & ML Capabilities

• Own and evolve personalization and recommendation systems that drive engagement and conversion across the customer journey
• Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning
• Develop causal inference methodologies to understand true incrementality of product changes.
• Ensure models are observable, explainable where needed, and continuously improved post-launch

Product Measurement & Impact

• Define product success metrics and measurement frameworks that align with business objectives
• Build scalable dashboards and monitoring systems that provide real-time visibility into product performance
• Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product optimization

Qualifications:

• 8+ years of experience in data science, with at least 3 years in leadership roles managing data scientists or ML engineers
• Proven track record building and deploying ML models in production, particularly in personalization, recommendation systems, or predictive modeling
• Deep expertise in experimentation and causal inference, including A/B testing, incrementality measurement, and statistical rigor
• Strong product sense and business acumen—ability to identify high-impact opportunities and translate them into data science initiatives
• Experience in consumer tech, e-commerce, or marketplace businesses where personalization and user engagement are critical
• Excellent communication skills—ability to explain complex technical concepts to non-technical stakeholders and influence product strategy
• Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch, TensorFlow)
• Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow)

Preferred requirements:

• PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field
• Experience with real-time ML systems and feature stores
• Background in recommendation systems or two-tower/multi-modal embeddings
• Familiarity with generative AI and LLM applications in product contexts
• Experience building data science teams from scratch or through periods of rapid growth
• Prior work in subscription businesses or retention-focused products
• Knowledge of modern product analytics tools (Amplitude, MixPanel, Looker)

What Success Looks Like

• 6 months: Established product data science roadmap aligned with business priorities; shipped at least one high-impact ML model to production; built strong partnerships with Product and Engineering leadership
• 12 months: Scaled the product data science function with key hires; delivered measurable improvements in personalization and customer engagement metrics; implemented robust experimentation frameworks used across product teams

Learn More About CookUnity

We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we’re looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale.

We hope this provides valuable insight into our culture and product vision. If this excites you, we’d love to connect!

Benefits

🩺  Health Insurance coverage

🌅 401k Plan

📈 We grow, you grow: Stock Options Plan granted on Day 1

🌟 Eligible for a bi-annual performance bonus

⛱ Unlimited PTO

🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

🐣 Paid Family leave

🕯 Compassionate Leave: 3-5 days each time the need arises

🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly

🧘🏽‍♀️ Wellness perks: access to fitness subsidies to build a healthy lifestyle

🤖 AI-forward workplace: enterprise access to ChatGPT and Claude to help you work smarter and grow faster.

👩🏾‍🏫 Personalized Spanish coach

🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

About the Role: 
We're seeking an experienced Staff Machine Learning Engineer to join our Engineering team. In this role, you'll drive the design and implementation of production machine learning systems within the Dragos platform. Working closely with Data Scientists, Data Engineers, and product teams, you'll build and deploy AI/ML capabilities that enhance threat detection, automate security analysis, and deliver actionable intelligence for Industrial Control System (ICS) and Operational Technology (OT) cybersecurity applications. 

Responsibilities: 

• Design and implement production-grade machine learning systems that expand Dragos product capabilities, with consideration for both cloud and resource-constrained on-premises environments. 
• Build and optimize ML model architectures for ICS/OT cybersecurity use cases, including threat detection, asset classification, behavioral analysis, anomaly detection, and natural language processing systems.
• Develop robust data pipelines and ML workflows that integrate with existing data infrastructure, supporting both real-time and batch processing requirements.
• Collaborate with Data Scientists to translate research concepts and prototypes into scalable, production-ready ML systems.
• Partner with Data Engineers to establish data contracts and implement observability frameworks for ML pipelines, including monitoring, versioning, and deployment best practices.
• Contribute to ML infrastructure improvements, including automated testing frameworks, CI/CD pipelines, and deployment strategies for containerized environments (Kubernetes, Docker).
• Evaluate and adapt state-of-the-art ML research and open-source models to domain-specific cybersecurity applications.
• Troubleshoot and optimize ML model performance in production environments, addressing issues related to latency, accuracy, and resource utilization. 

Qualifications: 

• 6+ years of engineering experience with at least 4 years focused on machine learning implementations in production environments.
• Strong software engineering foundation with expertise in Python and SQL as well as experience with at least one additional language (Go, Rust, Java, or JVM-family languages).
• Demonstrated experience building and deploying ML systems using modern frameworks and libraries (scikit-learn, PyTorch, TensorFlow, HuggingFace, or similar).
• Experience with LLMs, retrieval-augmented generation (RAG), or advanced NLP techniques is beneficial.
• Proven track record implementing ML solutions such as classification systems, time series analysis, anomaly detection, or NLP applications that deliver measurable business impact.
• Experience with MLOps practices, including model versioning, monitoring, pipeline orchestration, and deployment in high-reliability environments.
• Familiarity with data engineering concepts, including data pipelines, stream processing, message queuing, and working with medium-to-large scale datasets.
• Knowledge of containerized deployment solutions and cloud-native architectures.
• Strong communication skills with the ability to explain technical concepts to diverse stakeholders and collaborate effectively across teams.
• Cybersecurity domain knowledge, particularly in threat detection, threat intelligence, or ICS/OT operations, is a strong plus. 

Compensation: 

• Salary: $225,000
• Competitive Equity Package  
• Comprehensive Benefits Plan 

The Data Scientist I supports statistical analyses of large datasets, the development and deployment of Machine Learning (ML), multimodal Deep Learning (DL), and Artificial Intelligence (AI) solutions that improve the relevance and value of ads across our Ad Exchange, Contextual Platform, and Attention Measurement Platform. This role focuses on applying strong analytical foundations, building and evaluating ML and DL models, leveraging general AI concepts and techniques, while also partnering closely with the Engineering, Product, and Data Science team to improve ad-serving performance, operational decision-making and lead development of new AI products that best serve the business. 

The ideal candidate is curious, data-driven, and eager to develop a strong understanding of the advertising domain and the systems that power large-scale decision-making. You will work with large datasets, contribute to production AI systems, and gain hands-on experience across the ML lifecycle — from exploration to monitoring.

Note: GumGum fosters a flexible work environment, offering GumGummers the ability to work either in-office or remotely/from home. For this position, in-person/office collaboration is required 2 days per week, supporting a balanced approach to flexibility and team engagement.

What You'll Achieve

• Support the translation of business and product requirements into data-driven analyses and ML solutions
• Partner with Engineering team members and senior Data Scientists to develop, test, and deploy ML and DL models
• Conduct exploratory data analysis to inform feature development and modeling approaches
• Build, run, and maintain regular pipelines to analyze production data, generate KPIs, and prepare automatic retraining of existing models
• Query, clean, and structure large datasets using SQL, Spark, and cloud data platforms
• Train, evaluate, and iterate on traditional ML models and multimodal deep learning models under guidance from senior team members
• Design and maintain Looker dashboards and other Business Intelligence (BI) tools to track Key Performance Indicators (KPI) for key stakeholders
• Develop and deploy agentic pipelines and other LLM-powered applications, including prompt engineering, tool use, and evaluation of model outputs
• Contribute to existing Machine Learning Engineering (MLE) workflows for model training, deployment, and monitoring
• Document analyses, models, and broader learning to support knowledge sharing across the team and non-technical audiences
• Continuously expand on statistical and AI foundations while learning new AI/ML techniques, tools, and advertising-domain concepts

Skills You'll Bring

• Bachelor’s degree in a quantitative field (e.g., Statistics, CS, Math, Physics, or Economics).
• 1–2+ years in a data-driven role such as Analytics, Data Science, or ML Engineering.
• Proficiency in Python and experience applying ML/DL methods using libraries like scikit-learn, PyTorch, HuggingFace, or OpenCV.
• Dependable SQL skills and experience designing pipelines or DAGs using tools like Airflow or Astronomer.
• Exposure to cloud environments (AWS/GCP, Databricks, Snowflake) and large-scale query tools like Spark or Snowpark.
• Strong grasp of A/B testing, experimental design, and statistical concepts (regression, classification, optimization).
• Experience with LLM prompting and interest in frameworks like RAG, LangChain, or agentic systems.
• Ability to design dashboards for diverse audiences and collaborate effectively with Product and Engineering teams.

What We Offer

At GumGum, competitive base pay is a part of a total rewards package, which also includes benefits, an emphasis on recognition, development, and wellness. The reasonable estimated base pay range for this role is from $128,000-$130,000 annually. The actual amount may be higher or lower. Individual compensation will vary based on factors including, but not limited to, relevant qualifications, work location, and labor market conditions.

The total rewards package offered also includes an employer-matched 401(k) retirement plan, and, depending on the role, participation in a bonus, commission, or stock incentive program. Your recruiter can share more specifics during the hiring process. Learn more about our U.S. benefits & perks package at gumgum.com/benefits.

Founded in 2017, Trust & Will is the leading digital estate planning platform, trusted by over one million users. We provide modern, accessible solutions to help families protect their legacies with attorney-approved, legally valid documents tailored to individual state requirements. Our seamless online platform simplifies the estate planning and settlement process, empowering individuals to create wills and trusts while also partnering with financial advisors, attorneys, and institutions to make legacy planning more inclusive and affordable.

If you are passionate about contributing to a high-impact mission and want to work in a collaborative environment where your skills and expertise will be valued, we would love to hear from you!

About You

• You are a clear, concise communicator who can translate a complex regression or other mathematical reasoning into a one-paragraph recommendation for a non-technical stakeholder.
• You are a data scientist and analyst hybrid  equally comfortable building a causal inference model and presenting the business implication to a VP.
• You have startup experience and know what it means to stand up an analytics function, ship scrappy analyses, and build toward rigor  not wait for it.
• You treat experimentation as a discipline, not a buzzword. You design tests, size samples, interpret results correctly, and know when an A/B test isn't the right tool.
• You think in systems and funnels  you connect product behavior to business outcomes and are never satisfied stopping at the metric without asking why.
• You operate with high autonomy and you identify the most important question, define the approach, execute the analysis, and deliver the recommendation without a detailed playbook.
• You are AI-curious and actively explore how AI tools can accelerate your analytical workflows, automate repetitive queries, and surface insights faster.
• This position is available to candidates residing in the following states only: California (CA), Colorado (CO), Florida (FL), Georgia (GA), Idaho (ID), Illinois (IL), Maryland (MD), New Jersey (NJ), New York (NY), North Carolina (NC), South Carolina (SC), Pennsylvania (PA), Texas (TX), Vermont (VT)

About the Role

We're looking for a Senior Product & Growth Analyst to own the analytical engine behind Trust & Will's growth. This is a high-ownership role: you'll work across product, marketing, and revenue to understand what's driving conversion, retention, and lifetime value and you'll translate those findings into decisions that move the business.

This is not a reporting role. You will define the questions worth asking, build the models that answer them, run experiments to test the hypotheses, and guide the roadmap based on what the data shows. You'll partner closely with the Director of Data Engineering, product managers, and growth leadership  and you'll have direct access to senior stakeholders.

The core challenge is analytically interesting: estate planning is a low-frequency, high-intent product with a B2C direct channel and a growing B2B2C advisor network. Understanding how different user segments activate, convert, and retain  and which levers compound  requires real analytical depth. 

You'll have the data, the infrastructure, and the mandate to figure it out.

Product Analytics

• Instrument and analyze user behavior across the Trust & Will product  activation milestones, feature adoption, onboarding drop-off, and engagement patterns  using PostHog/Other.
• Develop and maintain the core product analytics dashboard and data models, enabling self-serve access for PMs, designers, and marketers.
• Identify friction points in the estate plan creation flow and quantify the impact of proposed product changes before and after release.

Growth & Funnel Analytics

• Own end-to-end funnel analysis from acquisition through plan completion and membership renewal identifying drop-off points, segmenting by channel and user type, and prioritizing optimization opportunities by expected impact.
• Build and maintain cohort models to track retention and engagement across consumer and advisor-sourced customers; surface early-warning signals for churn.
• For example, develop and maintain LTV models that account for plan type, channel, upsell pathways, and membership behavior  directly informing marketing budget allocation and partnership ROI decisions.
• Design and execute multi-touch attribution analysis across paid media, organic, AARP partnership, and advisor referral channels.

Experimentation

• Lead the experimentation program end-to-end: hypothesis formation, experimental design, sample size and power analysis, execution in PostHog/Others, statistical analysis, and business recommendation.
• Build guardrails and standards for when and how to run experiments  including when to apply experimental methods propensity score matching and when randomized testing isn't feasible.
• Partner with product and marketing teams to prioritize the test backlog based on expected impact and feasibility.

Data Science & Modeling

• Build predictive models for churn risk, conversion propensity, and upsell likelihood using early behavioral signals.
• Develop user segmentation frameworks that inform personalization, messaging, and product prioritization.
• Apply statistical rigor to all analytical work communicating uncertainty, flagging limitations, and recommending confidence thresholds before decisions are made.

Stakeholder Partnership & Communication

• Serve as the primary analytics partner for product and growth leadership, owning the analytical workstreams that support quarterly roadmap decisions.
• Prepare and deliver data-driven recommendations to senior stakeholders and the executive team  punchline first, minimum viable backstory, clear ask.
• Mentor junior analysts and product/eng on methodology, communication, and prioritization; help build team-wide analytical standards.

Qualifications

Core Experience

• 8-12+ years of experience in analytics, data science, or a closely related quantitative role.
• Prior experience in a high-growth startup environment  you've operated with limited resources, ambiguous data, and shifting priorities and delivered anyway.
• Demonstrated data science background: you've built predictive models, designed and analyzed experiments, and applied statistical methods to business problems in production settings.
• Experience owning an analytics domain end-to-end  not just answering requests, but generating the questions and driving decisions.

Technical Skills

• SQL: Advanced window functions, CTEs, complex joins, query optimization on large datasets.
• Python: Proficient pandas, statsmodels, scikit-learn, matplotlib/seaborn; you write clean, reproducible analytical code.
• Experimentation: End-to-end A/B test ownership, power analysis, and working knowledge of experimental methods.
  Product Analytics: PostHog, Amplitude, Mixpanel, or equivalent  funnel analysis, cohort analysis, event instrumentation.
• BI / Visualization:ThoughtSpot, Omni, or equivalent  building dashboards that enable self-serve, not just answering one-off requests.
• Data Modeling: Familiarity with dbt and the analytical data modeling - like ActivitySchema, Star Schema etc…

Bonus Points

• Experience in fintech, legaltech, insurtech, or another regulated consumer vertical.
• Familiarity with Bayesian methods or causal inference frameworks beyond standard A/B testing.
• Experience with product-led growth (PLG) motions or B2B2C business models.
• Background in subscription, membership, or low-frequency/high-intent consumer products.
• Contributions to building an analytics function from scratch  metrics frameworks, data dictionaries, experimentation standards.
• Comfort working with an AI Data Analyst tool in a self-serve analytics context.

Employee Benefits & Perks

• Compensation: Salary + Equity
  • Our salary range for this position is $140,000 - $190,000, in addition to compensation we also include an employee equity package as a component of our offer along with other benefits and perks outlined below. 
• PTO
  • Flexible time off that you are encouraged to use
  • Generous paid company holidays and breaks throughout the year 
  • Monthly friends & family day
  • Paid time off to volunteer in your community
• Health and Wellness Benefits
  • Exceptional health benefits including medical, dental, vision, life, and disability insurance - we cover 100% of premiums for employees and dependents on medical coverage
  • Mental health support through Spring Health, plus access to One Medical for primary care and Cleo for family planning and caregiving
  • Financial wellness benefits (unlimited 1:1 sessions with a UBS financial coach and employer-sponsored 401k with up to 4% company match)
• Extra
  • Flexible work schedule + hours
  • Family-friendly work environment. We support the complexity of a remote world with the needs of families
  • Up to $1,000 annually in learning & development reimbursement
  • Optional company-sponsored events and travel throughout the year
  • $500 Work from home stipend + Apple accessories 

About Trust & Will: 

• We are a remote-first company, giving our employees the flexibility they need to work in an environment that best suits their needs. Our hiring process is also conducted virtually unless otherwise noted. We are a company that was founded in San Diego, CA, and offer a collaborative co-working space that is available for you to use if you'd like but not required. #LI-Remote
• We are proud to be a certified B Corporation, using business as a force for good. We are committed to building a healthy, sustainable, and engaging working environment for all employees, their families, and communities. We publish an annual impact report to outline our positive contributions to our world and set an example for all employers.
• Trust & Will's mission is to help every family leave their legacy through affordable, accessible estate planning. That starts with the people we hire and the ways in which we support the development of their unique talents and capabilities. We are committed to prioritizing ways to make our company and industry more inclusive. This means we must be revolutionary in the way we value diversity to revolutionize our business sector. At Trust & Will, everyone has a seat at the table and space to be their authentic selves because only in a company that is inclusive and diverse can we truly stand in our members' shoes.

California Privacy Notice: Trust & Will collects personal information from applicants including identifiers, professional/employment history, and education information to evaluate qualifications and communicate about your application. California residents have the right to know what information we collect, request a copy, correct inaccuracies, or request deletion (subject to exceptions). To exercise these rights, contact legal@trustandwill.com. For more information, visit our privacy policy.

Trust & Will may use AI tools to assist with administrative recruiting tasks. All final hiring decisions are made by people. For accommodations, contact people-ops@trustandwill.com.

About the role

In the role of Senior Machine Learning Engineer for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California. You will lead the research, development, and test of advanced models, and work together with product and engineering partners to deliver tailored experiences for our fans across the anime ecosystem, including anime video recommendations, digital manga suggestions, merchandise personalization, anime-themed gaming, music, and more. This position will collaborate closely with scientists, engineers, product owners, to prototype innovative algorithms, evaluate their impact, and integrate them into production systems that drive user engagement, retention, discovery, and satisfaction.

We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. This position can be based in our Los Angeles or San Francisco offices.

Core Areas of Responsibility

• Research, design, and implement machine learning algorithms for recommendation systems, including collaborative filtering, content-based models, and deep learning, and generative recommendation approaches to personalize content discoveries.
• Co-develop end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment using scalable cloud platforms with engineers.
• Optimize models for accuracy, latency, and scalability to handle massive user interaction data from streaming and multi-platform, multi-domain experiences across the fandom.
• Integrate personalization solutions with other services, and implement monitoring for model performance, bias detection, and automated retraining.
• Collaborate on A/B testing, experimentation, and iterative improvements to refine recommendations based on user feedback and evolving content trends.

About You

We get excited about candidates, like you, because you have:

Experience: You bring 8+ years of hands-on experience in applied machine learning, with a proven track record in building recommendation systems or personalization engines, ideally in media, entertainment, or e-commerce platforms.

Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks, or similar. Experience with big data tools (e.g., Spark) and cloud infrastructure (e.g., AWS/GCP) for handling large-scale datasets.

Cross-Functional Collaborations: Experienced in partnering with data scientists and analysts, engineers, and product teams to deploy models that align with business objectives like increasing user retention and content consumption.

Communication Skills: Strong ability to document research findings, explain algorithmic choices, and present results to diverse stakeholders for effective adoption.

Educational Background: Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field, with publications or contributions in recommendation systems being a plus.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

#LifeAtCrunchyroll #LI-Hybrid

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, & co-founder, Tim Shi, an early member of Open AI.

We’ve assembled a world-class team of AI and ML experts, go-to-market leaders, and top-tier investors including Andreessen Horowitz, Greylock Partners, Sequoia, and former AT&T CEO John Donovan. Our valued customers include brands like Intuit, Cox Communications, Hilton, and Carmax and we’ve been recognized by Forbes and Bain Consulting as one of the top private AI companies in the world.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

Role Overview:

Cresta is expanding its Customer Success organization with a dedicated analytics function focused on customer value realization. As an AI Value Partner, Customer Analytics, you’ll be the technical engine behind measuring and storytelling customer impact—designing experiments, analyzing conversational and operational data, and building dashboards that quantify Cresta’s value.

You’ll sit within the Customer Success organization and partner closely with Customer Success Managers, Sales, Product, and Engineering. Your work will power ROI discussions, pilots, QBRs and ongoing strategic customer engagements.

This role is ideal for someone early in their data science career who enjoys hands-on analytics, problem-solving, and turning ambiguous business questions into clear, actionable insights.

Key Responsibilities:

Customer Analytics & Insight Generation

• Conduct exploratory data analysis (EDA) across conversational, operational, and performance datasets
• Translate ambiguous business questions into structured analytical problems
• Analyze how workflow, behavior, and product usage changes translate into business value

Experimentation & Pilot Measurement

• Design and analyze A/B tests and quasi-experiments to measure Cresta’s impact
• Establish baselines, metrics, and measurement plans for pilots
• Ensure results are statistically rigorous and easy for non-technical stakeholders to understand
• Build reusable templates and frameworks for consistent experimentation
• Work directly with customer to guide them towards our ideal experiment setup

Dashboards, Reporting & Automation

• Build and maintain dashboards tracking customer ROI
• Develop Python and SQL tools to improve repeatability, accuracy, and scalability
• Create standardized reporting packages for pilots, QBRs, and renewals

Modeling & Advanced Analytics

• Develop custom statistical or ML models (e.g., segmentation, predictive scoring, lightweight NLP)
• Maintain reusable modeling pipelines for value insights and roadmap analysis
• Partner with Engineering when guidance or productionization support is needed

Cross-Functional Collaboration

• Translate analyses into clear business and financial narratives
• Support CSMs with data and insights for strategic QBRs
• Partner with Product and Engineering on metrics, data availability, and analytics enhancements

Required Qualifications:

• 1–3 years of experience in a data-focused role or relevant academic experience
• Strong proficiency in SQL and experience working with large datasets
• Proficiency in Python (Pandas, NumPy, scikit-learn)
• Solid understanding of statistics, hypothesis testing, and experimental design
• Experience building dashboards in tools such as Hex, Looker, Tableau, or similar
• Strong communication skills with non-technical stakeholders
• Comfort working in a fast-paced, cross-functional environment

Preferred Qualifications:

• Experience with conversational data (call transcripts, chats) or text analytics
• Familiarity with causal inference, uplift modeling, or A/B testing frameworks
• Exposure to customer-facing analytics or support roles
• Experience with cloud data stacks (Snowflake, Redshift, etc.)
• Basic NLP or classification experience related to agent behavior or customer intent

Success Criteria:

Within 6–9 months, a successful hire will have:

• Built dashboards and reporting foundations used across Customer Success
• Implemented standardized pilot measurement and experimentation approaches
• Supported strategic customer analyses that improved renewals or expansion confidence
• Created scripts and automations that significantly reduce manual analysis
• Earned trust as the go-to analytics partner for Customer Success

Perks & Benefits: 

• We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs
• Flexible vacation time to promote a healthy work-life blend
• Paid parental leave to support you and your family
• Monthly Gym & Phone allowance
• Work from home office stipend to help you succeed in a remote environment
• Lunches and dinners included for in-office employees via Grubhub

Compensation At Cresta:

Cresta’s approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.

Compensation for this position includes a Base salary + Bonus + Equity

Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. Your recruiter can provide further details. In addition, total compensation includes a comprehensive benefits package for you and your family.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai

The Opportunity:

We are seeking a Senior Machine Learning Scientist to help accelerate drug discovery through advanced analytics and artificial intelligence. This role will develop predictive models and analytical methods that transform complex biological and chemical datasets into actionable insights that guide research decisions.

The Senior Machine Learning Scientist will work at the interface of data science, chemistry, and biology to support target discovery, compound optimization, and translational research. This position requires both strong machine learning expertise and the ability to collaborate effectively with experimental scientists to solve real-world scientific problems.

The successful candidate will contribute to building a data-driven discovery ecosystem where data, analytics, and experimentation continuously inform and accelerate one another.

Key responsibilities include:

Develop Predictive Models for Drug Discovery

• Design and implement machine learning models to predict compound activity, selectivity, and developability.

• Develop predictive frameworks for ADME/Tox, target engagement, and phenotypic screening outcomes.

• Apply advanced modeling approaches including deep learning, graph neural networks, and ensemble methods.

• Evaluate model performance and apply appropriate validation strategies.

• Work with data engineers and ML engineers to integrate models into discovery pipelines.

Analyze Complex Scientific Data

• Perform exploratory data analysis on chemical, biological, and phenotypic datasets.

• Integrate heterogeneous datasets including:

• Chemical structure and screening data.

• High-content imaging data.

• Structural biology and molecular simulation outputs.

• Identify patterns and relationships that inform scientific hypotheses.

Collaborate with Research Scientists

• Partner with medicinal chemists to support compound design and lead optimization.

• Work with biologists to interpret experimental results and identify new target opportunities.

• Translate scientific questions into computational modeling strategies.

Required Skills, Experience and Education:

• PhD in machine learning, computational biology, computational chemistry, computer science, statistics, or a related quantitative field.

• 4–8 years experience applying machine learning or advanced analytics to scientific datasets.

• Python and scientific computing libraries (NumPy, Pandas, SciPy).

• Machine learning frameworks (PyTorch, TensorFlow, scikit-learn).

• Model development, validation, and evaluation methods.

• Data visualization and exploratory analysis.

• Experience working with noisy and incomplete experimental datasets.

Preferred Skills:

• Cheminformatics or molecular modeling tools (RDKit, OpenEye, etc.).

• Multi-omics data analysis.

• Cloud computing environments.

• MLOps or scalable model deployment. 

  #LI-Hybrid  #LI-LN1

The Opportunity:

We are seeking a Principal Machine Learning Scientist to lead the development of advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex scientific datasets into predictive models that guide target discovery, compound design, and translational hypotheses.

Working closely with experimental scientists, the Principal ML Scientist will develop cutting-edge modeling approaches that integrate chemical, biological, and phenotypic data. The successful candidate will play a key role in advancing a data-driven discovery strategy by designing predictive models, deploying innovative algorithms, and translating insights into actionable decisions that improve the speed and success of the discovery of medicines for patients with RAS-driven cancers.

Key responsibilities include:

Scientific Leadership:

• Define and lead machine learning strategies that accelerate early-stage drug discovery.

• Identify opportunities where AI and advanced analytics can meaningfully improve scientific decision-making.

• Drive the adoption of innovative modeling approaches within multidisciplinary discovery teams.

Model Development:

• Develop predictive models for:

  • Compound activity, selectivity, ADME/Tox, and developability properties.

  • Target engagement, mechanism-of-action, and phenotypic datasets.

Apply modern ML techniques such as:

• Graph neural networks.

• Deep learning for molecular representation.

• Generative chemistry models.

• Active learning frameworks for experimental design.

Cross-Functional Collaboration:

• Partner with medicinal chemists to guide compound design and optimization.

• Work with biologists to interpret complex experimental datasets and generate mechanistic hypotheses.

• Collaborate with data scientists and engineers and ML engineers to deploy models into scalable discovery workflows.

Data Integration:

• Integrate heterogeneous datasets including:

• Chemical structure and screening data.

• Imaging and phenotypic screening data.

• Structural biology and molecular simulation outputs.

Required Skills, Experience and Education:

• PhD in machine learning, computational chemistry, computational biology, computer science, or a related quantitative discipline.

• 8+ years experience applying machine learning or advanced analytics to scientific problems.

• Demonstrated experience working with chemical or biological datasets in drug discovery or related domains.

• Strong expertise in:

  • Python-based ML ecosystems (PyTorch, TensorFlow, scikit-learn).

  • Data analysis and scientific computing (NumPy, Pandas).

  • Deep learning and representation learning techniques.

• Strong understanding of early-stage drug discovery workflows.

• Ability to translate biological or chemical questions into computational frameworks and predictive models.

• Proven ability to communicate complex computational insights to.

• Passion for scientific innovation and a relentless commitment to improving patient outcomes.

Preferred Skills:

• Proven track record of applying advanced AI/ML approaches (deep learning, generative modeling, structure-based ML) to drug discovery or related life sciences domains.

• Experience with cheminformatics or bioinformatics toolkits is highly desirable.

• Familiarity with cloud computing and scalable ML workflows is a plus

• Ability to work at the interface of computational and experimental science. 

  #LI-Hybrid  #LI-LN1

About the role

In the role of Data Scientist, you will report to the Director of Machine Learning and Data Science. We are considering applicants for the location(s) of Los Angeles, CA or San Francisco.

We are seeking a Data Scientist with skills and experience in using User Behavior Analytics and Modeling to kick start our effort to detect and deter account sharing by leveraging platform-collected data such as login patterns, device usage, IP addresses, and viewing behaviors. This position focuses on uncovering insights from large datasets to inform machine learning models that identify anomalous sharing activities, ultimately supporting revenue growth and subscriber retention strategies inspired by industry leaders like Netflix and Disney+.

Core Areas of Responsibility

• Conduct exploratory data analysis on user session logs to establish baselines for normal and anomalous behaviors.
• Develop predictive models using statistical and machine learning techniques to forecast and segment user sharing patterns.
• Design and conduct experiments to validate the model accuracy and operations effectiveness.
• Collaborate with cross-functional teams to define data requirements and create frameworks for ongoing behavioral monitoring.
• Build visualizations and reports to communicate insights on user engagement and potential sharing risks to stakeholders.
• Ensure data privacy compliance while optimizing data pipelines for efficient operations.

About You

We get excited about candidates, like you, because you have the following:

• Experience: You have 5+ years in data science roles focused on behavioral analytics, preferably in tech or streaming industries, with proven success in user behavior modeling, anomaly and fraud detection, and related applications.
• Technical Skills: Proficient in Python for data analysis and modeling, SQL for database querying, and tools like Tableau or matplotlib for visualization, with experience in machine learning libraries such as xgboost, scikit-learn, and pytorch for modeling.
• Cross-Functional Collaborations: Skilled at partnering with engineering, product, and legal teams to align analytics with business objectives and integrate findings into product features.
• Communication Skills: Adept at presenting complex behavioral insights in clear, actionable formats to non-technical audiences through reports and visualizations.

Education Background: Hold a master's degree in data science, statistics, computer science, or a related field, with coursework in behavioral economics or psychology being advantageous.

About the Team

You will join an interdisciplinary team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and ML/AI to create transformative solutions. Our team delivers both consumer-facing product features that enhance the streaming experience for millions of users and stakeholder-oriented solutions that empower internal teams with actionable insights. From building personalized recommendation systems to developing innovative tools like our stakeholder-facing chatbot, we combine cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Collaboration, creativity, and a commitment to excellence define our team’s culture as we work together to push the boundaries of what’s possible in streaming and data-driven decision-making.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

#LifeAtCrunchyroll #LI-Hybrid

We are hiring an Applied Scientist to help advance personalization across the Crunchyroll ecosystem. In this role, you will lead the scientific development of recommendation, ranking, and decisioning solutions that improve how fans discover and engage with anime series/movies, manga, merchandise, games, and other areas in the anime fandom. You will partner closely with Machine Learning Engineers, Product, Engineering, Marketing, and Content stakeholders to make Crunchyroll the ultimate destination for anime experience.

About the role

In the role of Senior Applied Scientist for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in our Center for Data and Insights. You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ideal for someone who enjoys combining strong scientific rigor with product thinking to improve user discovery, engagement, retention, and long-term fan value.

You will work across multiple user touchpoints, including app and web interfaces, lifecycle and promotional email campaigns, and flywheels that connect video, ecommerce, manga, and adjacent experiences. You will help define what great personalization looks like at Crunchyroll, build the evidence to prove impact, and collaborate with engineering partners to ensure the resulting solutions can be productionized effectively.

This position is based in our Los Angeles office, but we will consider our San Francisco office as a secondary location. We work a hybrid schedule, in-office three days a week: Tuesday, Wednesday, and Thursday. 

Core areas of responsibility

• Lead the research and development of recommendation, ranking, retrieval, and personalization methods tailored to Crunchyroll use cases across streaming, manga, ecommerce, and lifecycle marketing surfaces.
• Frame ambiguous business and product questions into clear scientific problems, hypotheses, success metrics, and experimentation plans.
• Design and run robust offline evaluation frameworks for recommender systems, including relevance, diversity, novelty, coverage, calibration, and long-term value metrics.
• Partner with Product, Analytics, and Engineering to define online experiments, interpret results, and turn learnings into roadmap decisions and model improvements.
• Develop user, content, and contextual understanding through feature design, representation learning, segmentation, and behavioral analysis.
• Prototype and evaluate a range of approaches, including collaborative filtering, content-based methods, sequence modeling, deep learning, bandits, causal or uplift methods, and LLM-enabled recommendation techniques where appropriate.
• Analyze user feedback loops and cross-domain interactions to improve discovery across video, merchandise, manga, and other ecosystem experiences.
• Work closely with Machine Learning Engineers to translate promising research into production-ready solutions on our in-house recommendation platform.
• Communicate scientific findings, model tradeoffs, and business implications clearly to technical and non-technical stakeholders.
• Help establish best practices for experimentation, reproducibility, model governance, and scientific documentation within the personalization and recommendations function.

About you

We get excited about candidates, like you, because you have:

Experience: You bring 5+ years of experience in applied machine learning, recommendation systems, search/ranking, experimentation, or a closely related area, with a track record of driving measurable product impact.

Scientific Depth: You have strong foundations in machine learning, statistics, experimental design, and causal thinking, and you know how to choose the right level of modeling complexity for the problem at hand.

Recommendation Expertise: You have hands-on experience with at least some of the following: collaborative filtering, retrieval and ranking systems, representation learning, sequence / generative models, bandits, graph methods, or personalization for consumer products.

Technical Skills: You are highly proficient in Python and comfortable working with common ML libraries such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar tooling. Experience working with SQL, distributed data processing, and cloud-based ML workflows is strongly preferred.

Experimentation Mindset: You know how to design offline and online evaluations, reason carefully about metrics, and connect experimental findings to user and business outcomes.

Cross-Functional Collaboration: You have experience partnering effectively with engineers, product managers, analysts, marketers, and business stakeholders to move from idea to execution.

Communication Skills: You can explain sophisticated modeling decisions and ambiguous findings in a clear, decision-oriented way to diverse audiences.

Educational Background: You hold an MS or PhD in Computer Science, Machine Learning, Statistics, Operations Research, Economics, or a related quantitative discipline, or you bring equivalent applied industry experience.

Nice to have

• Experience personalizing content, commerce, media, entertainment, gaming, or subscription products at scale.
• Familiarity with recommender-system failure modes such as popularity bias, cold start, sparse feedback, and feedback loop effects.
• Experience with multi-objective optimization, constrained ranking, or balancing short-term engagement with long-term user value.
• Exposure to generative AI, representation learning, or LLM applications that support recommendation and personalization workflows.
• Published research, patents, or open-source contributions in recommendation systems, personalization, applied machine learning, or experimentation.

About the team

Our centralized DS/ML team serves stakeholders across Finance, Product, Engineering, Marketing, Creatives, and Content Operations with data-driven and ML/AI-powered solutions. Within that broader organization, the Personalization and Recommendation group is building the next generation capabilities to power tailored fan experiences across every major user interface and lifecycle touchpoint. Today, the team includes engineers focused on operationalizing our recommendation platform with strong engineering excellence. This Applied Scientist role complements that foundation by bringing deeper scientific ownership to modeling strategy, evaluation, and experimentation, while partnering closely with an additional MLE hire to accelerate production impact.

Why this role is exciting

• You will help define personalization strategy across multiple surfaces instead of optimizing a single narrow funnel.
• You will work on problems that span content discovery, user engagement, retention, and cross-domain ecosystem value.
• You will influence both what we build and how we measure success, with strong exposure to partners across the business.
• You will join at a formative moment, with the opportunity to shape team standards, technical direction, and long-term roadmap.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

#LifeAtCrunchyroll #LI-Hybrid

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands—increasing reliability and performance while lowering costs and enabling confident, data-driven decision-making in dynamic environments.

The Role

As a Machine Learning Engineer at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to both the customer-driven projects and the enduring products of the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will inform, envision, and help extend Striveworks’ core software products. You will work alongside data scientists, software engineers, and DevOps engineers to transform machine learning models into operational capabilities.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome-driven and are passionate about applying both software engineering and data science to solve real-world problems. You know that building customer-centric solutions, communicating clearly, and capturing repeatable value into productized capabilities are all important. 

Your day-to-day will include:

• Developing machine learning models and custom analytics that are applied to image, video, text, geospatial, time series, and structured data
• Orchestrating and automating complex data engineering and analytic pipelines
• Envisioning, specifying, and, at times, designing and implementing core product functionality
• Conducting mission-critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on-site work environment at our office in northwest Austin, TX. You will be expected to travel up to 30% of the time.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

We value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• BS degree in computer science, machine learning, or a related discipline and 2+ years of relevant experience
• Experience contributing to data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
• Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
• Proficiency in Python and exposure to libraries like TensorFlow, PyTorch, and/or scikit-learn
• Exposure to modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Advanced degree in data science, machine learning, computer science, or a related discipline
• Excellence in Python and deep knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
• Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
• Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes, infrastructure as code, major cloud architectures)
• Experience with machine learning applied to imagery and/or video data
• Experience building agentic systems, agentic workflows, or AI agents
• Experience defining, scoping, planning, and delivering complex technical solutions
• Experience delivering technology solutions in secure government environments

The anticipated base pay range for this position is $140,000–$165,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Check us out on Built In!

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.

The Role

As a Machine Learning Engineer at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to both the customer-driven projects and the enduring products of the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will inform, envision, and help extend Striveworks’ core software products. You will work alongside data scientists, software engineers, and DevOps engineers to transform machine learning models into operational capabilities.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome driven and are passionate about applying both software engineering and data science to solve real-world problems. You know that building customer-centric solutions, communicating clearly, and capturing repeatable value into productized capabilities are all important. 

Your day-to-day will include:

• Developing machine learning pipelines and custom analytics that are applied to image, video, text, geospatial, time series, and structured data
• Orchestrating and automating complex data engineering and analytic pipelines
• Envisioning, specifying, and, at times, designing and implementing core product functionality
• Conducting mission-critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on-site work environment at customer sites at Schofield Barracks in Oߵahu, Hawaiߵi. You will be expected to travel up to 30% of the time, including some international travel.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• BS degree in computer science, machine learning, or a related discipline and 2+ years of relevant experience 
• Experience contributing to data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics)
• Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.)
• Proficiency in Python and exposure to libraries like TensorFlow, PyTorch, and/or scikit-learn
• Exposure to modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.)
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Advanced degree (e.g., MS, MEng, PhD) in computer science, machine learning, data science, or a related discipline
• Excellence in Python and deep knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
• Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular)
• Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [K8s], cloud architectures)
• Experience with machine learning applied to imagery and/or video data
• Experience building agentic systems, agentic workflows, or AI agents
• Experience defining, scoping, planning, and delivering complex technical solutions
• Experience delivering technology solutions in secure government environments

The anticipated base pay range for this position is $175,000–$205,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Check us out on Built In!

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

You get energy when you see someone on your team crack a problem they couldn’t have solved six months ago because you helped them get there. You care about technical rigor, but you care even more about outcomes. You know that a well-scoped project with clear success criteria will beat a brilliant but ambiguous one every time. And you’re not afraid to roll up your sleeves and lead the hard modeling work yourself when the situation calls for it.

At Fixify, we’re building an AI-native IT automation platform where data science sits at the center of the product, not bolted on. Our models run in production. Our experiments drive real decisions. And the team’s work directly shapes how customers experience Fixify. As a Data Science Manager, you’ll own both the development of the team and the quality of its output — ensuring research translates into reliable, production-ready systems that Product, Engineering, and Customer Success depend on.

This is a player-coach role. You’ll lead and grow a team of data scientists while staying close to complex research, modeling and experimental design. You’ll set the standards for how work gets done — from experimentation practices to model handoff — and you’ll be the person who unblocks the team when things stall. If you want to build a team that ships with confidence and grows while doing it, this is the role.

What we can do for you

• Give you a team of data scientists to grow and a mandate to set the standard for how data science gets done at Fixify.
• Put you at the intersection of Product, Engineering, and Customer Success, where your team’s work directly shapes the product.
• Let you stay hands-on technically — this is not a step-away-from-the-work role. You’ll lead complex research alongside your team.
• Surround you with peers and leaders who value rigor, clarity, and shipping work that drives measurable impact.
• Give you the autonomy to design and refine processes and practices as Fixify scales.

What you can do for us

• Lead, mentor, and manage a team of data scientists — setting expectations, giving feedback, and building people up.
• Own execution quality for data science delivery, ensuring research translates into production-ready, well-documented systems.
• Partner with Product to define research priorities and with Engineering to ensure models integrate cleanly into production.
• Step into complex modeling and research efforts yourself when senior technical judgment and experience are required.
• Build and improve the team’s processes — including experimentation standards, methodology reviews, documentation practices, and model handoff workflows.

What you should bring with you

• Experience leading and developing data scientists, including coaching, performance feedback, and career progression.
• Expert-level knowledge of statistical modeling, machine learning, and GenAI techniques.
• Strong proficiency in Python and SQL, with deep fluency in libraries like Pandas, NumPy, and scikit-learn.
• Experience shipping models to production and a clear understanding of what it takes to make research work reliably at scale.
• A track record of designing evaluation frameworks, monitoring systems, and logging strategies for production models.
• The ability to scope ambiguous problems, prioritize effectively, and keep a team aligned in a fast-moving environment.
• Clear communication skills — you can translate between data science, product, and engineering without losing the thread.
• Experience working cross-functionally with Product, Engineering, and business stakeholders.
• Comfort operating with ambiguity and shifting priorities; you lead through it rather than waiting for it to resolve.
• A genuine belief that quality, reproducibility, and rigor aren’t nice-to-haves — they’re how you build trust in data science.

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.

The Role

As a Data Scientist at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to the projects, products, and direction of the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will work as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers to transform machine learning models into functional products.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome driven and are passionate about applying both software and data science to solve real-world problems. You know that being customer focused, rigorous in approach, clear in communication, and able to identify repeatable value opportunities are all critical to success. You are able to sense the needs of the customer, identify evolving demands, and then synthesize that feedback into actionable suggestions for Striveworks’ product teams.

Your day-to-day will include:

• Developing and validating machine learning models and custom analytic algorithms that are applied to image, video, text, geospatial, time series, and structured data
• Implementing AI-based software solutions for cloud and edge environments
• Conducting mission-critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on-site work environment at our office in northwest Austin, TX. You will be expected to travel up to 30% of the time.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• BS degree in computer science, machine learning, mathematics, or a related discipline and 2+ years of relevant experience 
• Proficiency in machine learning and data science, and applying both to image and video data
• Proficiency in implementing and analyzing data structures and algorithms
• Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
• Exposure to software development life cycle and tools (e.g., Git, Agile) 
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Advanced degree (e.g., MSA, MEng, PhD) in computer science, machine learning, mathematics, or a related discipline
• Experience deploying machine learning and data science, and applying both to production environments
• Exposure to DevOps and Cloud infrastructure (e.g., Docker, Kubernetes, CI/CD, major cloud providers)
• Experience processing a variety of unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, geospatial, graphs, or telemetry signals)
• Experience building AI agents and agentic workflows
• Experience implementing ETL pipelines, data pipelines, and/or workflow automation
• Experience developing software in a compiled programming language (e.g., Go, Rust, C++, Java, etc.)
• Experience building full-stack applications (i.e., back end, front end, REST)
• Experience delivering technology solutions in secure government environments
• Experience working with federal, state, and/or local government customers

The anticipated base pay range for this position is $140,000–$165,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

What you’ll do:

• Design, implement, and maintain internal software libraries and applications as well as computing infrastructure to enable engineers to solve problems faster and more efficiently. Promote the use of shared computational infrastructure, tools, and practices across engineering teams within the Flight Sciences department.
• Develop processes and software tools to improve the reproducibility and traceability of computations. Drive the implementation of such tools.
• Promote a culture of software excellence across the engineering organization.
• Understand the needs of various engineering teams to efficiently utilize High-Performance Computing (HPC) resources, and make informed decisions on infrastructure solutions to ensure optimal resource utilization and cost savings.
• Maintain and administer on-premises HPC resources. 
• Advocate for engineering and computing needs with the company-wide IT department.

What you need:

• Master's or Ph.D. in Aerospace Engineering, Mechanical Engineering, Computational Engineering, or a related field.
• 5+ years of experience as a user and developer of scientific/engineering software for flight sciences or similar disciplines (such as aerodynamics, acoustics, control, loads, thermal analysis, mass properties, vehicle simulation, etc.) in a fast-moving environment.
• Demonstrated experience in developing computing software and infrastructure, with proficiency in the scientific Python ecosystem (NumPy, SciPy, Pandas, Scikit-learn, TensorFlow/PyTorch, VTK).
• Demonstrated experience in standard best practices in software development, including version control, CI/CD, software testing, environment management.
• Demonstrated experience with the design and administration of HPC systems, either on-premise or cloud (AWS preferred). Knowledge of Linux administration, high speed network interconnects, parallel file systems, and MPI required.
• Experience with HPC management software (Slurm/PBS/Torque, OpenHPC/Bright, Warewulf/XCat, Spack/EasyBuild, Lmod).
• Good understanding of enterprise IT and common network security practices.
• Excellent problem-solving skills and ability to work collaboratively in a team environment.

Bonus qualifications:

• Experience as an engineer in one or more of the following areas of aircraft design - aerodynamics, conceptual design, rotor/propeller design, vehicle simulation, loads and dynamics, structural design, stress analysis, GNC.
• Contributions to open source scientific software projects.
• Experience with MATLAB and Simulink.
• Proficiency in one or more compiled languages (e.g. C/C++, Fortran, Rust).
• Familiarity with databases (SQL, NoSQL, time-series) and database application design (ORM/ODM).
• Experience with software packaging (Pip, Conda, Spack) and containerization technologies (Docker/Singularity/Shifter) for scientific software.
• Familiarity with software configuration management tools (Chef/Puppet/Ansible).
• Familiarity with common CI/CD tools and practices (TeamCity/Jenkins, Artifactory, Docker, etc.).
• Experience with analysis tools and workflows for aircraft/rotorcraft design (aerodynamics, CFD, GNC, loads, structural analysis, CAD, mass properties, etc.).

At Archer, we aim to attract, retain, and motivate talent with the skills and leadership needed to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s strategy. For this position, we are targeting a base pay range of $162,800 - $217,600. Actual compensation offered will be determined by job-related knowledge, skills, and experience.        

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

As a Senior Data Scientist, you will play a pivotal role in advancing Reify Health’s data-driven solutions for clinical trials. In this position, you will drive the development of statistical models and machine learning algorithms to improve patient enrollment and trial management. You’ll work in a highly regulated healthcare data environment, ensuring compliance with privacy standards while innovating on predictive analytics. This role involves close collaboration with cross-functional teams (especially ML Engineering) to translate complex data insights into practical, impactful tools for the clinical research community.

What You’ll Be Working On

• Site Randomization Forecasting: Develop/enhance forecasting models for site randomization and enrollment trends, enabling better planning and resource allocation across trial sites. 
• Patient Matching/Ranking Algorithms: Support projects to build algorithms that intelligently match patients to (or rank patients for) appropriate clinical trials, enhancing recruitment efficiency and patient inclusion. 
• Develop Other Advanced Statistical Models: Create and refine predictive models (Bayesian inference, regression analysis, time-series forecasting) to address other key clinical trial challenges and improve decision-making. 
• AI Monitoring and Bias Detection: Implement processes to monitor machine learning models in production, detecting bias or performance drift and ensuring models remain fair, accurate, and compliant. 
• Data Pipeline & Tooling Development: Build and optimize data pipelines and analytical workflows using tools like AWS Athena, Redshift, SageMaker, and dbt, enabling scalable model training and deployment. 
• Regulatory Compliance in Data Science: Ensure all data science practices align with HIPAA, GDPR, and other privacy regulations, integrating compliance considerations into model development and data handling. 
• Cross-Functional Collaboration: Work closely with machine learning engineers, product managers, and other stakeholders to integrate models into products and clearly communicate insights and recommendations. 

What You Bring to OneStudyTeam

• Education: Master’s or Ph.D. in Statistics, Data Science, Computer Science, or a related quantitative field (or equivalent professional experience). 
• Experience: 5+ years of hands-on data science or analytics experience, preferably in a healthcare, clinical research, or other highly regulated data environment.
• Statistical & ML Expertise: Strong foundation in statistical modeling and machine learning techniques, including experience with Bayesian methods, regression analysis, and time-series forecasting. 
• Model Monitoring & Fairness: Proficiency in evaluating model performance and bias, with the ability to implement AI monitoring tools and bias mitigation strategies to ensure ethical and reliable outcomes. 
• Technical Toolset: Advanced programming skills in Python (with libraries such as scikit-learn, PyMC, mlforecast, etc.) and SQL, as well as familiarity with data transformation tools like dbt. 
• Cloud & Data Infrastructure: Hands-on experience with cloud-based analytics and ML services, especially AWS tools (Athena for querying, Redshift for data warehousing, SageMaker for model development/deployment). 
• Regulated Data Handling: Experience working with sensitive healthcare or clinical trial data under regulations like HIPAA and GDPR, demonstrating a deep commitment to data privacy and security best practices. 
• Collaborative Communication: Excellent teamwork and meticulous verbal/written communication abilities, with a track record of partnering with engineering and product teams to translate data science work into actionable business solutions. 
• Domain Knowledge: Understanding of clinical research or health-tech environments is highly valuable, including insight into clinical trial operations and a passion for improving patient outcomes through data.

The expected salary range for this role is $140,000 - $190,000 USD per year for full time team members.

#LI-Remote

Build, Deploy, and Maintain AI for an Unpredictable World

Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective.

With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands, increasing reliability and performance while lowering costs—and enabling confident, data-driven decision-making in dynamic environments.

The Role

As a Data Scientist at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to the projects, products, and direction of the company. You will represent Striveworks as a technology builder on projects and solutions that leverage Chariot, our proprietary AI operations (AIOps) platform, and you will inform and contribute to future capabilities of that platform. You will work as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers to transform machine learning models into functional products.

You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome driven and are passionate about applying both software and data science to solve real-world problems. You know that being customer focused, rigorous in approach, clear in communication, and able to identify repeatable value opportunities are all critical to success. You are able to sense the needs of the customer, identify evolving demands, and then synthesize that feedback into actionable suggestions for Striveworks’ product teams.

Your day-to-day will include:

• Developing and validating machine learning models and custom analytic algorithms that are applied to image, video, text, geospatial, time series, and structured data
• Implementing AI-based software solutions for cloud and edge environments
• Conducting mission-critical fieldwork in support of customers and other stakeholders

This position offers a hybrid/on-site work environment at customer sites at Schofield Barracks in Oߵahu, Hawaiߵi. You will be expected to travel up to 30% of the time, including some international travel.

The Right Fit

In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. 

Collectively, we value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results.

Here’s what we’re looking for:

• BS degree in computer science, machine learning, mathematics, or a related discipline and 2+ years of relevant experience 
• Proficiency in machine learning and data science, and applying both to image and video data
• Proficiency in implementing and analyzing data structures and algorithms
• Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
• Exposure to software development life cycle and tools (e.g., Git, Agile) 
• Active Secret (or above) US security clearance
• Due to the nature of this role, candidates must have US citizenship

The Wish List

We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of:

• Advanced degree (e.g., MS, MEng, PhD) in computer science, machine learning, mathematics, or a related discipline
• Experience deploying machine learning and data science, and applying both to production environments
• Exposure to DevOps and Cloud infrastructure (e.g., Docker, Kubernetes, CI/CD, major cloud providers)
• Experience processing a variety of unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, geospatial, graphs, or telemetry signals)
• Experience building AI agents and agentic workflows
• Experience implementing ETL pipelines, data pipelines, and/or workflow automation
• Experience developing software in a compiled programming language (e.g., Go, Rust, C++, Java, etc.)
• Experience building full-stack applications (i.e., back end, front end, REST)
• Experience delivering technology solutions in secure government environments
• Experience working with federal, state, and/or local government customers

The anticipated base pay range for this position is $175,000–$205,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.

The Benefits

• Medical/dental/vision insurance
• Voluntary life, long-term disability, accident, and hospital indemnity insurance
• HSA and FSA (including dependent care FSA) plans 
• 401(k) plan
• Unlimited PTO
• Paid parental leave

Check us out on Built In!

Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.

If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us.

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.

Striveworks is a participating employer in the E-Verify program.

Location: Mountain View, CA
Commitment: On-site
Duration: 12 weeks starting in 2026
Conversion Opportunity: High-performing interns will be evaluated for full-time offers

About the Program

We're launching our 2026 Engineering Internship Program, a fast-paced, high-impact opportunity designed for aspiring engineers who want to build real products, ship meaningful features, and accelerate their path into a full-time role. Over the course of 12 weeks, you’ll work closely with experienced engineers, gain hands-on mentorship, contribute directly to production systems, and help solve real challenges across NewsBreak's ecosystem. This is a paid, on-site internship based in our Mountain View headquarters. Top-performing interns will be considered for full-time offers at the conclusion of the program.

Highlighted Projects：

You will be matched to a team based on skills, interests, and business needs. Sample projects include:

MSP Monetization – Mountain View, CA

MSP is our next-generation, AI-powered monetization platform that empowers publishers to unlock their full revenue potential with unmatched transparency and control. It combines intelligent optimization, real-time insights, and seamless ad management to help publishers confidently scale their business and maximize long-term growth.

Newsletter Systems – Mountain View, CA

Aigeon.ai is an exciting new product built by NewsBreak, the leading platform for local news and information serving tens of millions of users across the United States. Aigeon is reimagining the newsletter and content-monetization space via AI: simplifying creation, audience growth, and monetization of newsletters for content creators and small media brands. 

NBot – Mountain View, CA

Drive the optimization of conversational experiences that power our next-generation news recommendation engine, enabling more personalized, intuitive, and intelligent user interactions.

AI Initiatives – Mountain View, CA

This initiative explores cutting-edge NLP, generative AI, and multimodal technologies to power the next generation of content intelligence. The project includes building AI-driven content generation capabilities that significantly expand the content supply while enhancing accuracy, quality, and user relevance. The goal is to create scalable AI systems that deliver meaningful impact to tens of millions of NewsBreak users.

Foundational Requirements:

• Currently in the final semester of a Master’s or PhD program in Computer Science (or a closely related field), or recently graduated from a top-tier university.
• Strong proficiency in at least one major programming language (e.g., Python, Java, C++, Go).

Preferred Qualifications:

• Coursework, academic research, or hands-on projects in Machine Learning, Artificial Intelligence, NLP, Recommendation Systems, or Large Language Models
• Experience using ML frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn)
• Familiarity with data pipelines, model training, or evaluating ML models
• Prior internships or project experience involving ML-powered features, AI agents, or AIGC systems

We’re seeking builders with diverse technical backgrounds, whether you’re a full stack engineer, machine learning engineer, or mobile engineer, who are excited to solve real problems with cutting-edge AI technologies. If you’re passionate about the latest advancements in AI, have built your own apps or projects, or naturally think with an entrepreneurial, ownership-driven mindset, you’ll thrive in this program. We value candidates who are curious, hands-on, and eager to turn ideas into impact.

Hourly Pay for internship: $40-$50