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.

About the team  

Our Warfighter Systems division is pioneering a future where mixed reality (MR), creates immersive, intuitive, and life-saving technologies. By seamlessly integrating real-time data with cutting-edge visualization tools, we are empowering warfighters with unparalleled situational awareness, enhanced training experiences, and operational superiority. This team is consistently pushing the boundaries of what's possible and shaping a future where technology and defense unite to protect our nation.  If this starts to excite you, we invite you to read further!

About the job  

We are seeking a highly skilled and experienced Systems Engineer to design, develop, and validate sophisticated models for our complex electro-mechanical systems, with a particular focus on sensors, cameras, and displays. The ideal candidate will leverage first-principles physics, empirical data, and advanced mathematical techniques to create high-fidelity, predictive models used across the entire product lifecycle – from concept exploration and design optimization to control system development and virtual testing. This role is critical in accelerating our product development cycles, improving system performance, and ensuring robust and reliable operation. 

What you'll do

• Model Development: 
  • Develop mathematical and behavioral models for various sensor types (e.g., IMU, Lidar, Radar, Ultrasonic, environmental sensors), capturing characteristics such as noise, latency, calibration, field of view, and transfer functions.
  • Create detailed camera models, encompassing optics, image signal processing pipelines, distortion, resolution, dynamic range, and temporal characteristics.
  • Integrate individual component models into comprehensive system-level simulations, accurately representing their interactions and overall system dynamics.
  • Develop and maintain Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) simulation environments. 

• Model Validation & Calibration:
  • Design and execute experiments to gather real-world data for model parameter identification, calibration, and validation.
  • Perform rigorous statistical analysis to quantify model accuracy, uncertainty, and fidelity against empirical measurements.
  • Identify discrepancies between model predictions and real-world behavior and iteratively refine models for improved accuracy. 

• Performance Analysis & Optimization:
  • Conduct trade-off studies using models to optimize system architecture, component selection, and control strategies based on performance, cost, power consumption, and reliability metrics.
  • Predict system performance under various operating conditions and environmental factors.
  • Perform sensitivity analyses to understand the impact of individual parameters on overall system behavior.
  • Support root cause analysis of system issues using simulation. 

• Collaboration & Communication:
  • Collaborate closely with cross-functional teams including Electrical, Mechanical, Controls, Software, and Test Engineers to define model requirements and integrate models into the broader development process.
  • Clearly communicate complex modeling concepts, results, and limitations to both technical and non-technical stakeholders through presentations and detailed documentation. 

• Tooling & Methodologies:
  • Select, evaluate, and implement appropriate modeling and simulation tools and techniques.
  • Develop custom scripts and tools to enhance modeling capabilities and automate workflows.
  • Stay abreast of industry best practices, new modeling methodologies, and emerging simulation technologies. 

Required Qualifications

• 6+ years of experience in system modeling, simulation, and analysis, particularly with electro-mechanical systems.
• Demonstrated experience in developing models for at least two of the following:

• • Sensors: IMUs (accelerometers, gyros), Lidars, Radars, Ultrasonic sensors, microphones, etc. (noise characteristics, drift, latency, sensor fusion).
  • Cameras: Optical models, image processing pipeline models, distortion, noise, dynamic range, rolling shutter effects.
  • Display: See/pass-through near eye display architectures, optical modeling, validations, & human perception 

• Strong theoretical foundation in classical and modern control systems, dynamics, signal processing, and numerical methods.
• Proficiency in primary modeling and simulation tools such as MATLAB/Simulink (Simscape a plus), Python (SciPy, NumPy, Pandas), or C/C++.
• Experience with model validation against experimental data and statistical analysis techniques.
• Excellent problem-solving skills, with an ability to apply first principles to complex engineering challenges.
• Strong communication and interpersonal skills, with the ability to work effectively in a team environment. Strong technical communication skills to collaborate effectively with cross-functional teams. 
• U.S. Person Status: Due to government contract requirements, candidates must be a U.S. Person (U.S. Citizen or Green Card holder).
• Bachelor's or Master's degree in Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, Physics, or a related quantitative field. 

Preferred Qualifications

• Ph.D. in a relevant engineering or scientific discipline.
• Familiarity with Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) testing methodologies and platforms (e.g., dSPACE, National Instruments).
• Knowledge of advanced control techniques (e.g., adaptive control, optimal control, robust control) and estimation algorithms (e.g., Kalman filters, particle filters).
• Experience with machine learning techniques for model identification, surrogate modeling, or data-driven predictions.
• Exposure to systems engineering processes, requirements management, and configuration control.

About the team  

Our Warfighter Systems division is pioneering a future where mixed reality (MR), creates immersive, intuitive, and life-saving technologies. By seamlessly integrating real-time data with cutting-edge visualization tools, we are empowering warfighters with unparalleled situational awareness, enhanced training experiences, and operational superiority, primarily through our EagleEye augmented reality system. This team is consistently pushing the boundaries of what's possible and shaping a future where technology and defense unite to protect our nation.  If this starts to excite you, we invite you to read further!

About the job  

We are seeking a highly skilled and experienced Systems Engineer to design, develop, and validate sophisticated models for our complex electro-mechanical systems, with a particular focus on sensors, cameras, and displays. The ideal candidate will leverage first-principles physics, empirical data, and advanced mathematical techniques to create high-fidelity, predictive models used across the entire product lifecycle – from concept exploration and design optimization to control system development and virtual testing. This role is critical in accelerating our product development cycles, improving system performance, and ensuring robust and reliable operation. 

What you'll do

• Model Development: 
  • Develop mathematical and behavioral models for various sensor types (e.g., IMU, Lidar, Radar, Ultrasonic, environmental sensors), capturing characteristics such as noise, latency, calibration, field of view, and transfer functions.
  • Create detailed camera models, encompassing optics, image signal processing pipelines, distortion, resolution, dynamic range, and temporal characteristics.
  • Integrate individual component models into comprehensive system-level simulations, accurately representing their interactions and overall system dynamics.
  • Develop and maintain Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) simulation environments. 

• Model Validation & Calibration:
  • Design and execute experiments to gather real-world data for model parameter identification, calibration, and validation.
  • Perform rigorous statistical analysis to quantify model accuracy, uncertainty, and fidelity against empirical measurements.
  • Identify discrepancies between model predictions and real-world behavior and iteratively refine models for improved accuracy. 

• Performance Analysis & Optimization:
  • Conduct trade-off studies using models to optimize system architecture, component selection, and control strategies based on performance, cost, power consumption, and reliability metrics.
  • Predict system performance under various operating conditions and environmental factors.
  • Perform sensitivity analyses to understand the impact of individual parameters on overall system behavior.
  • Support root cause analysis of system issues using simulation. 

• Collaboration & Communication:
  • Collaborate closely with cross-functional teams including Electrical, Mechanical, Controls, Software, and Test Engineers to define model requirements and integrate models into the broader development process.
  • Clearly communicate complex modeling concepts, results, and limitations to both technical and non-technical stakeholders through presentations and detailed documentation. 

• Tooling & Methodologies:
  • Select, evaluate, and implement appropriate modeling and simulation tools and techniques.
  • Develop custom scripts and tools to enhance modeling capabilities and automate workflows.
  • Stay abreast of industry best practices, new modeling methodologies, and emerging simulation technologies. 

Required Qualifications

• 9+ years of experience in system modeling, simulation, and analysis, particularly with electro-mechanical systems.
• Demonstrated experience in developing models for at least two of the following:

• • Sensors: IMUs (accelerometers, gyros), Lidars, Radars, Ultrasonic sensors, microphones, etc. (noise characteristics, drift, latency, sensor fusion).
  • Cameras: Optical models, image processing pipeline models, distortion, noise, dynamic range, rolling shutter effects.
  • Display: See/pass-through near eye display architectures, optical modeling, validations, & human perception 

• Strong theoretical foundation in classical and modern control systems, dynamics, signal processing, and numerical methods.
• Proficiency in primary modeling and simulation tools such as MATLAB/Simulink (Simscape a plus), Python (SciPy, NumPy, Pandas), or C/C++.
• Experience with model validation against experimental data and statistical analysis techniques.
• Excellent problem-solving skills, with an ability to apply first principles to complex engineering challenges.
• Strong communication and interpersonal skills, with the ability to work effectively in a team environment. Strong technical communication skills to collaborate effectively with cross-functional teams. 
• U.S. Person Status: Due to government contract requirements, candidates must be a U.S. Person (U.S. Citizen or Green Card holder).
• Bachelor's or Master's degree in Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, Physics, or a related quantitative field. 

Preferred Qualifications

• Ph.D. in a relevant engineering or scientific discipline.
• Familiarity with Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) testing methodologies and platforms (e.g., dSPACE, National Instruments).
• Knowledge of advanced control techniques (e.g., adaptive control, optimal control, robust control) and estimation algorithms (e.g., Kalman filters, particle filters).
• Experience with machine learning techniques for model identification, surrogate modeling, or data-driven predictions.
• Exposure to systems engineering processes, requirements management, and configuration control.

IMC Americas, Inc. has multiple openings for Trader (REQ#4461664101) in Chicago, IL and Brooklyn, NY.

Your Core Responsibilities

• Develop, maintain, and enhance mathematical models, strategies, and trading system components for quantitative proprietary trading in collaboration with developers (10%).
• Independently design and implement changes to trading models, strategies, and systems from end-to-end, including conceiving of proposed changes, creating a testing plan, and performing tests, and implementing changes (15%).
• Analyze, interpret, and model financial, economic, and industry data to optimize trading and maximize revenue generation using existing internal tools (15%).
• Create custom analysis tools for use at the firm to perform research beyond available analysis tools (5%).
• Prepare and present high-quality financial analysis and reports following IMC global guidelines (15%).
• Perform daily operational tasks on the trading desk, ensuring systems are running correctly and escalating as needed to designated contacts (15%).
• Supervise and mentor graduate traders and interns (10%).
• Train graduate traders through the firm's traineeship (5%).
• Contributing to planning and prioritization decisions of future projects on their trading desk (5%).
• Monitoring and managing a trading firm's risk exposure (5%).

Partial telecommuting permitted. Multiple positions available. Requisition Number: 4461664101

Your Skills and Experience

This position requires a Bachelor's degree, or foreign equivalent, in Mathematics, Econometrics, Computer Science, Financial Engineering, Physics, or similarly quantitative and mathematical field and one (1) year of experience in the job offered or a related position.

Must have experience in the following skills:

• Developing, maintaining, and enhancing mathematical models, strategies, and trading system components for quantitative proprietary trading in collaboration with developers;
• Operating trading strategies through a range of market circumstances, having a thorough understanding of risk at any point in time;
• Rolling out and verifying new features on trading strategies;
• Managing a trading firm's risk exposure;
• Using Python and python coding libraries, including Pandas, NumPy, and SciPy to assist in quantitative analysis; and
• Experience trading products and navigating compliance regulations in trading markets. 

Requires FINRA Certifications: (1) SIE and (2) Series 57.

#LI-DNI

About Skyloom 

Skyloom, an IonQ company, is a telecommunications company founded with the mission to develop, deploy, and operate one of the fundamental pieces of tomorrow's space communication infrastructure to provide data transport services on a planetary scale. If you have a strong sense of purpose, focus, urgency, and willingness to compete, or if working on space lasers excites you, join our team to develop the future generation of space communication technology.

Skyloom is building the orbital infrastructure for the next renaissance in global connectivity. As Earth’s first space-based telecommunications company, we deliver fiberless, planetary-scale data transport that dramatically increases bandwidth, availability, and resiliency—while reducing latency and total cost of operations.

Our proprietary optical technology enables secure, ultra-high-capacity connections across our end-to-end, multi-orbit network or within your own infrastructure, unlocking a new standard for global communications.

Location: This role will be onsite in our Broomfield, Colorado office. 
Travel: Up to 5%
Job ID:  1450

The Role

We are seeking a V&V and Operations Tools Developer to design, build, and maintain the critical software infrastructure and tooling required for the early design verification, system deliveries validation, and operational monitoring of our flight systems. This role is fundamental to achieving mission assurance by automating testing, supporting complex physical testbeds involving external sensors and actuators, and facilitating early hardware/software integration.

Responsibilities 

• Develop high-quality, robust automation scripts and tools to support early hardware integration testing and interface verification.
• Apply Object- Oriented Programming(OOP) principles to design scalable and reusable software libraries for hardware interface communication and complex data acquisition from the testbed.
• Design and implement automated test sequences for health integration and performance verification of flight systems, analyzing feedback loops, sensor readings, and actuator responsiveness.
• Manage and configure the physical testbed infrastructure, including integrating and calibrating external sensors, actuators, and instrumentation required for comprehensive system testing.
• Develop and maintain the tools and framework necessary to execute Hardware-in-the-Loop (HIL) testing, including environment simulation, real-time data injection, and automated fault insertion.
• Implement minimal services to facilitate data handling, instrument control, and integration between various V&V tools in a distributed physical testbed environment.
• Utilize Docker to containerize development, testing, and V&V environments, ensuring consistency and reproducibility across the organization.
• Administer and maintain Linux operating systems that host the V&V testbeds, simulation platforms, and operational tools.
• Configure and troubleshoot networking protocols and services (TCP/IP, UDP, etc.) to ensure reliable connectivity between test equipment, flight hardware interfaces, and data centers.

Qualifications

• Systemic Mindset: Ability to view the flight system and its V&V testbed not as separate components, but as an integrated system, understanding dependencies, interfaces, and optimizing end-to-end performance.
• Python: Advanced proficiency for tool development and scripting. 
• Strong understanding and application of Object-Oriented Programming (OOP).
• Linux: Experience as user, basic administration for troubleshooting in various distributions.
• Bash scripting for system automation and pipeline execution.
• Experience with Docker for containerizing environments.
• Minimal experience designing or interacting with REST microservice.

Preferred Qualifications

• Experience with Observability Stacks (e.g., ELK/Influx/Grafana) for monitoring testbed health, data logging, and visualizing operational metrics.
• Prior experience in the validation of control software or safety-critical systems.
• Familiarity with data analysis libraries such as Pandas and plotting libraries like Matplotlib for analyzing sensor and performance data.
• Understanding of Distributed Systems architecture and challenges.
• Documentation Automation: Experience integrating documentation tools like Sphinx, Asciidoc or Markdown.

Compensation 

The approximate base salary range for this position is $114,477 - $150,248. The total compensation package includes base, bonus, equity, and a range of benefit options found on our career site.  

**Benefits will be provided by Skyloom, Inc., an IonQ Company, and will differ from the benefits listed on the IonQ website.**

We are looking for a Senior Staff Software Engineer for Application Engineering. As a Sr Software Engineer on the Applications Engineer team, you’ll be part of a cross-functional team whose mission is to deliver real-world applications and value from the leap forward in computing enabled by quantum technology. 

We don't just build the world's best quantum computers - we apply cutting edge quantum computing tools to real world problems. Until now, our team of Applications Scientists have been building prototypes, working closely with our customers. Our new department, Applications Engineering, will ultimately help transform proven quantum computing use-cases pioneered by our scientists into production applications, making those innovations available to more people and businesses by packaging and deploying these tools as SaaS applications.

But first, we must mature existing proof-of-concept quantum code into production grade applications. As a hands-on team lead for a new engineering team, you will work on enhancing developer experience (DevEx) by applying best practices to research-grade code. You will also set up CI / CD pipelines, software packing tools, and pre/post flight tests for new algorithms as they go into deployment. Where possible you will also be in charge of optimizing and parallelizing traditional algorithms, to reduce pre-processing and post-processing workloads. You will spearhead a new team taking newly invented quantum applications, and turning them into well defined modules of reliable SaaS applications. Think of it as being a forward-deployed engineer for quantum computing applications; the strongest candidates will be generalists with wide-ranging interests. 

This team will work closely with Developer Tools, Infrastructure, and Product teams to solve problems by choosing the right technologies, and standardizing and automating those solutions. The right engineer will be comfortable working on refining chemistry simplification via Quantum Computing tool one quarter, and turning a novel quantum topology solver into a service the next - and love pair programming with scientists. They’ll bring the quantum expertise; you bring the deep and broad experience in classical programming.

Responsibilities:

• Partner with Application scientists to help deliver cutting-edge solutions for customers
• Elevate Applications code quality generally through architectural review, code review, standards, and best practices
• Improve Applications pace of delivery by creating CI / CD pipelines and other packaging automation, as well as test infrastructure and coverage
• Help productize computing code, especially improving data processing in pre-quantum and post-quantum processing steps
• Work closely with peers in Applications, Developer Tools, and Product teams to share best practices and feedback on internal tools
• Reporting to the Director of Application Engineering, help hire and mentor developers on the team

You’d be a good fit with:

• 12+ years of experience as a backend or full-stack developer, preferably in Python or Golang
• 5+ years of experience in setting up and maintaining CI / CD pipelines, in Github Actions, Jenkins, or similar tools
• 5+ years of experience in C/C++ or Rust
• 3+ years of experience in Docker, k8s, or similar containerization technologies
• A track record of shipping containerized applications that solve real business problems
• Previous work in scientific computing, quantum computing, or a related field
• Daily usage of augmented coding tools like Claude or Gemini 

You’d be a great fit with:

• 5+ years of experience in scientific computing, especially with data analysis using numpy, pandas, or similar
• Experience in HPC or performance optimization
• Experience in converting traditional algorithms into CUDA, OpenMP workflows, or similar parallelization experience
• Experience with workflow orchestration engines like Airflow, Dagster, or Temporal

Location: This position can work onsite or hybrid from our office in Bothell, WA; College Park, MD; or Boulder, CO
Travel: 5% for quarterly travel for collaboration 
Job ID:  1312

The approximate base salary range for this position is $192,979 - $252,659. The total compensation package includes base, bonus, and equity.

Your Core Responsibilities

• Collaborate with Traders to evaluate and enhance the performance of IMC’s existing proprietary trading models using advanced mathematical and analytical methods.
• Design quantitative methods to gather and analyze historical market data, trading statistics or new data sources and use the result of that research as the basis for new trading strategies.
• Translate trading strategies into mathematical models, algorithms, and other complex computational programs to realize the combined vision of the trading team.
• Build custom computational data analysis tools to explore new quantitative research ideas; design mathematical models to test, visualize and refine trading ideas before implementation.
• Apply rigorous analytical and quantitative techniques to solve complex problems presented by new and existing proprietary trading strategies.
• Coordinate with developers to implement new and improved quantitative trading models and launch them into production on IMC’s proprietary trading platform
• Conduct all quantitative trading research, development, and implementations according to internal best practices to keep IMC’s trading ecosystem logical and consistent.

Partial telecommuting permitted. Multiple positions available.

Quantitative Researcher (Requisition ID: 4453347101)

Your Skills and Experience

This position requires a PhD, or foreign equivalent, in Finance, Financial Mathematics, Financial Engineering, Statistics, Computational Mathematics or similarly quantitative and mathematical field.

Must have demonstrated experience in each of the following skill(s):

• Application of analytical and quantitative techniques to solve complex problems;
• Designing and implementing mathematical models and algorithms, including linear modeling, convex optimization, and numerical methods for large-scale data and parameter estimation;
• Developing and using computational data analysis tools for research;
• Statistical programming techniques (including Python or C++) and designing and executing independent quantitative research projects, including formulation of hypotheses, development of models, empirical testing, and clear documentation of results;
• Time series analysis, applied statistics, and theoretical mathematics (such as probability, measure theory/real analysis, and linear algebra);
• Implementing algorithms, conducting data analysis, and building research pipelines using numerical and scientific computing libraries (such as NumPy, pandas, SciPy) and version control (such as Git);
• Experience with time series modeling and forecasting, including stochastic processes and state-space or related frameworks, such as applied to real-world data; and
• Conducting literature reviews and replicating and extending prior work with methodological rigor and reproducibility.

#LI-DNI

Role & Team

As an Applied Analytics Lead at Overstory, you will play a critical role in linking our customer impact, data analytics, and product direction. Overstory’s vegetation intelligence technology provides industry-leading insights that help utilities improve their operational and strategic decisions. You’ll be the “tip of the spear,” working directly with utility customers to conceive of and deliver actionable analyses to solve their most pressing problems, while helping identify which solutions should inform our next generation of product capabilities.

This is a strategically significant hands-on role for someone who wants to move from advising on problems to owning them: using analytics to help utility customers turn Overstory insights into action today, and using what we learn to shape the product that scales that impact tomorrow. 

This is a great opportunity for someone who loves solving client problems through analytics AND is interested in a product or operational role where they can build new capabilities at a high-growth mission-driven company. Additional highlights of this role include:

• Ownership: Innovate on, deliver, and grow a critical capability for a fast-growing business from customer problem-solving through to scalable productization. 
• Impact: Make a tangible, scalable contribution to climate resilience in the power sector. 
• Skills: Leverage your advisory and analytical toolkit while building product judgment, technical depth, startup operating experience, and your craft with AI tools. 
• Trajectory: Grow your career at a high-growth company, with potential pathways into Product, Customer Success, Sales, or Strategy functions.

Time Zone Requirement: North America (EST strongly preferred)

What You’ll Do

Drive customer impact through analytics

• Own end-to-end analytical work for existing and new utility customers, in close partnership with Customer Success.
• Solve customer problems by bringing your full client advisory toolkit to bear: understand their goals and constraints, structure and analyze the problem, communicate and iterate on results, and guide to take action and create real-world impact 
• Analyze large, complex datasets from Overstory’s platform, customer systems, and third-party sources and deliver outputs in the format that creates the most value: Excel models, presentations, in-product workflows, and lightweight prototypes that can inform future product development.
• Bring creativity, drive, and a curious, customer-first mindset to everything you do, ensuring customers maximize the value of our vegetation risk insights 

Help shape what we build next

• Identify patterns across customer needs, use cases, and analytical projects, and translate them into clear opportunities for product development.
• Help determine which customer solutions should remain bespoke, which should become repeatable workflows, and which should evolve into scalable product capabilities.
• Partner closely with product teams to define frameworks, metrics, prototypes, and product ideas that improve how customers use and realize value from Overstory’s insights.
• Bring a deep understanding of customer decision-making, data needs, and operational realities into roadmap discussions and product prioritization. 

Scale our ability to serve customers in novel ways

• Create processes, templates, and playbooks that become a core part of our customer experience.
• Improve how we deliver customer-facing analyses and experiences across teams.
• Strengthen the analytics workflows and infrastructure that support both customer impact and future productization.

Skills & Experience

• Passionate about tackling climate challenges with data-driven solutions.
• 3-5 years of professional experience managing customer relationships as a trusted advisor/counterpart; extremely comfortable in front of customers.  
• Excited by the opportunity to use customer-facing analytical work to influence product direction and help build more scalable solutions over time. 
• Strong experience working with large, complex datasets to create valuable business insights; can break down large problems into smaller, easier-to-digest parts 
• Proficiency in Excel for data modeling and analysis. 
• Demonstrable track record of learning new technical analysis tools (e.g., SQL, Python / pandas, geospatial analysis tools) 
• Demonstrable experience (or at a minimum a serious interest in) leveraging AI tooling to accelerate business impact.
• Proven ability to solve ambiguous problems, listen actively, collaborate with stakeholders, and lead through influence. 
• Excellent communication skills, with the ability to translate technical findings for non-technical audiences

Nice To Have

• Experience with Python / pandas, SQL, and/or GIS
• Background in utility operations, infrastructure, or vegetation management
• Prior work in a high-growth startup or mission-driven company
• Exposure to remote sensing, AI, or geospatial analytics
• Experience working in a management consulting firm

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

Role

We’re seeking a Senior Data Analyst specializing in product analytics to help shape the future of our revenue cycle management platform. In this highly cross-functional role, you'll collaborate with product managers, engineers, and business stakeholders to gauge opportunities, guide strategy, and inform decisions with data. You’ll explore new datasets, build prototypes, monitor performance, and measure the product impact. This role offers a unique chance to take a leading role in delivering on an ambitious product roadmap using data to enhance the operational efficiency of healthcare providers.

**This role is fully remote within the US**

What You'll Do

• Partner with product managers and engineers to translate business goals into analytical requirements, perform exploratory analyses, and clearly communicate findings to support strategic decisions
• Design experiments to answer business questions, including defining key metrics and applying appropriate statistical techniques to analyze results
• Prototype analytics solutions and data products to accelerate product development
• Translate analytical findings into compelling data stories through clear visualizations that help stakeholders quickly grasp trends, patterns, and implications
• Becoming an expert in our data stack: how we get the data from customers, how we normalize that data, and how internal teams and customers consume that data
• Building, maintaining, and testing data models which support reporting and analytics.
• Uphold high standards for code quality and documentation, while contributing to a culture of peer review and continuous learning

What You Bring

• 3-5+ years' experience as a data analyst or product data scientist (or, if your y-intercept is lower, evidence that your slope is super steep)
• Strong technical skills: querying data with SQL, transforming data with dbt to shorten time to insight, performing analysis with python, and communicating findings with compelling data visualizations
• Masters in statistics or other relevant fields preferred
• Ownership: Build and own features from start to finish.
• Strategic mindset: strong ability to connect analytics to business understanding and provide actionable insights.
• Scrappiness: Navigate ambiguity effectively, understanding when it’s necessary to piece solutions together on the fly, and be able to do so.
• Product focus: How can we maximize the utility and value we deliver to our end users?
• Familiarity with experiment design and statistical analysis

Nice To Haves

• Experience with health system clinical and/or revenue cycle data is preferred

Our Tech Stack

• Data Visualization: Hex and Evidence
• Analysis: Python & Data Science libraries (numpy, pandas, etc)
• Pipelines: Snowflake, dbt, airflow, git, and AWS

Compensation

$160,000 - $190,000

#LI-Remote

Overview

As a member of our Sales Strategy and Operations team, you will have an integral role in driving the insights, operations, and strategy that enables Sales to run better, faster, and smarter. Sales Strategy and Operations is an excellent platform to learn how a business really runs.  

You will be joining the Sales Strategy and Operations team as a high-impact contributor, gaining exposure to a wide variety of challenges, processes, and data that makes the engine of this Sales organization hum. As an Associate on the team, you will lead cross-functional initiatives from ideation to analytics to recommendations to drive impact across the sales organization.

Why the data team? 

Data is the foundation of our go-to-market strategy. It supports all parts of our sales motion, including: 

• Populating and maintaining an accurate universe of buyers 
• Segmenting our sales team and defining sales representative patches 
• Identifying and facilitating key growth opportunities, e.g., entering markets in previously untapped geographies 
• Creating customer profiles to identify and target high value buyers

We recognize the importance of data to our scalability and success, and we aim to make it a core competency of our business. 

What You’ll Do

• Design a global data structure: design and manage data core to the success of our 500+ member sales team. Define a multi-source data structure that solves for both business priorities (update cadence, quality thresholds) and technical constraints. 
• Source and evaluate vendors: conduct market analyses to compare vendor capabilities to satisfy key business requirements; work with marketers and sales teams to evaluate vendor quality and present recommendations to the leadership team. 

• Improve data quality and value: identify opportunities to use data to grow revenue. Find new methods for lead generation. Increase sales prospecting efficiency by improving the accuracy of our data. 

… and more! 

Requirements

• Technical skills and previous exposure to SQL and/or Python/Pandas is required. Brownie points for advanced proficiency.
• You’re a high-impact self-starter: You take initiative to move projects forward and operate with high autonomy. You can take multiple different sources and products and “plumb” them together to make new tools quickly.
• You bridge the gap between the technical and the non-technical. You can translate a sales rep’s "wish list" into technical requirements for engineers and then explain the results back to a business audience.
• 2-4 years of professional experience in data analytics, product management, or high-impact consulting.
• Academic Background: Bachelor’s or Master’s degree in a technical or quantitative discipline (e.g., Computer Science, Engineering, Mathematics, or Economics) is a plus.

US Employee Benefits

About the Role

We're looking for a backend software engineer with strong data analysis skills to join our camera fleet management team. You'll build the data infrastructure and analytical tools that power our safe release operations across a million+ camera devices. This role combines traditional backend engineering with data pipeline development, log analysis, and metrics-driven insights.

Camera firmware releases include critical updates like new AI models, and understanding their impact requires sophisticated data analysis at scale. You'll develop the pipelines, dashboards, and analytical tools that help us detect anomalies, measure release health, and ensure every deployment is successful. Your work will directly support data-driven decision making for releases that impact our customers and our reputation.

Every release decision we make affects hundreds of thousands of cameras in the field. The data pipelines you build and the insights you surface directly determine whether we can release confidently or need to halt a problematic rollout. You'll be the engineering force behind our data-driven release culture.

You'll work closely with the Systems Software Engineer leading the team to build robust data infrastructure—from ingestion pipelines processing high-volume logs to SQL queries surfacing critical insights to real-time monitoring dashboards.

What You'll Do

• Build data pipelines: Design and implement data workflows using technologies like Kafka, Firehose, or Spark to process release metrics and device telemetry at scale
• Develop analytical tools: Create Python-based analysis tools using pandas and SQL to identify release issues, detect anomalies, and measure fleet health
• High-volume log analysis: Build systems to ingest, process, and analyze logs from millions of devices using technologies like OpenSearch, text clustering, and AI-based techniques
• Create monitoring infrastructure: Develop Grafana dashboards and alerts that surface critical metrics and anomalies in real-time
• Support release operations: Provide data-driven insights during releases, helping the team make informed decisions about rollout speed and risk
• Design test infrastructure: Build test bench setups and CI pipelines that validate releases before they reach production
• Query and optimize: Write efficient SQL queries against timeseries databases to extract insights from large-scale device data

Must-Haves

• BS/MS in Computer Science (or similar degree).
• 3+ years experience of industry experience in distributed software engineering.
• Strong Python skills: Proficiency in Python for data analysis, particularly with libraries like pandas
• SQL expertise: Experience writing complex SQL queries and queries for time-series analysis
• Backend engineering fundamentals: Solid software engineering skills—this is a backend role that happens to involve data, not a pure data engineering position
• Data pipeline experience: Familiarity with pipeline technologies like Kafka, Firehose, or Spark
• Log analysis at scale: Experience with high-volume log analysis technologies such as OpenSearch, text clustering, or AI-based log analysis techniques
• Timeseries databases: Experience working with timeseries databases and temporal data
• Metrics & observability: Hands-on experience with Grafana or similar monitoring tools
• Anomaly detection: Understanding of anomaly detection techniques and their practical application
• Coding-based analysis: Preference for solving problems through code rather than manual analysis
• Must be willing and able to work onsite five days per week.

Nice-to-Have

• Experience with Go
• Background in statistics or experimental design
• Familiarity with A/B testing and statistical inference
• Experience with CI/CD systems
• Knowledge of test automation frameworks
• Understanding of distributed systems

US Employee Benefits

Verkada is committed to fostering a workplace environment that prioritizes the holistic health and wellbeing of our employees and their families by offering comprehensive wellness perks, benefits, and resources. Our benefits and perks programs include, but are not limited to:

• Healthcare programs that can be tailored to meet the personal health and financial well-being needs - Premiums are 100% covered for the employee under at least one plan and 80% for family premiums under all plans
• Nationwide medical, vision and dental coverage
• Health Saving Account (HSA) with annual employer contributions and Flexible Spending Account (FSA) with tax saving options
• Expanded mental health support
• Paid parental leave policy & fertility benefits
• Time off to relax and recharge through our paid holidays, firmwide extended holidays, flexible PTO and personal sick time
• Professional development stipend
• Fertility Stipend
• Wellness/fitness benefits
• Healthy lunches provided daily
• Commuter benefits

Additional Information

• We do sponsor and take over sponsorship of employment visas for this role. If we make you an offer, we will make every reasonable effort to get you a visa.

The Role

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. As a Quantitative Researcher, you’ll operate near the tip of the spear in a collaborative, dynamic environment. This includes close partnership with other researchers, traders, and engineers on quantitative problem-solving, trading strategy generation, back-testing, statistical analysis, and system design. Our environment of collaborative innovation and intellectual curiosity allows us to share in our victories while continually challenging ourselves to stretch the limits of our creativity. Take advantage of this opportunity to apply the scientific method to business problems as part of one of our Quant teams at CTC! 

We prioritize team matching at the outset of our hiring process, thoughtfully considering which of our two teams (Vol Overlay or Delta Force) offers the best fit for each candidate’s strengths and interests while also aligning to the firm’s highest priority needs. 

What We’re Looking For   

We are seeking a Quantitative Researcher who can seamlessly blend academic rigor with practical application in our fast-paced trading environment. This individual will partner with our Trading and Technology teams to strengthen, scale, and evolve the firm's trading capabilities. The ideal candidate will possess a unique combination of analytical prowess, programming skills, and eye for business, driving innovation and results in quantitative finance. 

Responsibilities 

• Analyze market data to come up with economic and microstructure hypotheses 
• Build predictive and explanatory models to describe financial markets 
• Add revenue by applying thorough research processes to real life business problems 
• Contribute to ongoing improvement of research and trading infrastructure 

Qualifications 

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Applied Mathematics, or Operations Research) 
• Proven ability to conduct independent, high-quality research 
• Exceptional ability to communicate complex ideas and research results, both in writing and verbally 
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes. 
• Demonstrated expertise in applying quantitative modeling techniques to large, complex datasets 
• Strong track record of publications in an industry setting 
• Advanced Python programming skills 

Nice to Have 

• Proficiency in C++ 
• Experience in financial markets 
• Experience using NumPy and Pandas libraries 
• Experience with the software development lifecycle 

Summary

We are looking for a software engineer to build internal tools that help our battery algorithm team work faster and smarter. You will develop applications for test data analysis, visualization, and documentation, incorporating AI powered capabilities where they accelerate engineering workflows. This is a software engineering role: you will write clean, maintainable code, build intuitive interfaces, and integrate modern AI services into practical tools that engineers actually use.

What You Will Do

• Build Python based applications for analyzing and visualizing large scale battery test data, including time series datasets.
• Develop web based GUIs that let engineers explore, filter, and interact with test results.
• Integrate LLM APIs (e.g., OpenAI, Anthropic) into workflows to automate documentation, extract context from requirement sheets, change reports, and code repositories.
• Create data pipelines that pull from multimodal sources and present actionable insights.
• Collaborate with algorithm engineers and test engineers to understand their pain points and build tools that solve real problems.
• Continuously improve tooling based on user feedback and evolving team needs.

Minimum Qualifications

• B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Mechanical Engineering, or related field.
• 3+ years of professional software development in Python, including data analysis and visualization libraries (pandas, matplotlib, plotly, etc.)
• Experience building web based tools or applications with a frontend component (e.g., React, Streamlit, Dash, or similar)
• Strong debugging and problem solving skills.
• Comfortable working with APIs and integrating third party services.

Preferred Qualifications

• Experience integrating LLM APIs or AI services into applications (prompt engineering, API orchestration, retrieval augmented generation)
• Familiarity with time series data analysis
• Experience with document automation or generation (Word, PDF, slides)
• Exposure to battery management systems or embedded systems workflows• Experience with CI/CD, version control best practices, and collaborative development environments

At.Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

What We Offer

.Monks has provided a compensation range that represents its good faith estimate of what Media.Monks may pay for the position at the time of posting. .Monks may ultimately pay more or less than the posted compensation range. The salary offered to the selected candidate will be determined based on job-related factors, but not based on a candidate’s sex or any other protected status.

Cupertino, CA

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.

Position Overview:

We’re looking for a Senior Data Implementation Engineer to help lead and accelerate Acadian’s data transformation efforts. This role is central to reimagining and rebuilding our data platform so that we can continue to scale our investment research, production data workflows, and operational capabilities in a rapidly evolving landscape.

You’ll be hands-on in designing and implementing modern data pipelines and platform capabilities using tools such as Apache Arrow, Polars, Dagster, and other emerging technologies. You’ll also help shape how we use AI-assisted development tools, such as Claude & ChatGPT, and related automation approaches, to improve the speed, quality, and maintainability of data pipeline development.

This is a senior engineering role for someone who can operate across both strategy and execution: deeply understanding existing systems, designing pragmatic transition paths, mentoring others, and building reliable, scalable, high-performance data infrastructure that directly supports Acadian’s quantitative investment process.

Acadian supports a hybrid work environment; employees are on-site in the Boston office 3 days a week.

What You’ll Do

• Lead Data Pipeline Design and Implementation
  • Design, build, and optimize robust data pipelines that are reliable, scalable, observable, and performant. Use modern data engineering tools and patterns to support investment research, production workflows, and downstream analytics.
• Drive System Modernization
  • Deeply understand existing data systems, identify architectural limitations, and lead the transition toward more modern, maintainable, and efficient data architectures.
• Shape Technical Direction
  • Partner with Data Platform Engineering, Data Analysis, and investment teams to define implementation patterns, pipeline standards, and architectural approaches that can scale across the organization.
• Apply AI Tooling to Engineering Workflows
  • Use AI-assisted development tools such as Claude, ChatGPT, or similar technologies to accelerate pipeline development, automate repetitive workflows, improve documentation, generate tests, and enhance developer productivity.
• Mentor and Lead Others
  • Provide technical guidance to junior and mid-level engineers. Help raise the engineering bar through code reviews, design discussions, pairing, documentation, and thoughtful mentorship. Lead small project teams or workstreams when needed.
• Improve Reliability and Operational Excellence
  • Develop systems with strong testing, monitoring, lineage, data quality checks, and operational supportability. Help ensure that data pipelines are resilient, transparent, and easy to maintain.
• Collaborate Across Teams
  • Work closely with stakeholders across technology, data, research, and investment teams to understand requirements, resolve ambiguity, and deliver solutions that create measurable business value.
• Continuously Improve the Platform
  • Identify opportunities to simplify, automate, and improve the data ecosystem. Champion practical innovation while balancing speed, stability, maintainability, and long-term architectural quality.

We’re Looking for Teammates With

• Bachelor’s degree in a relevant field

• A strong background in data engineering, data platform implementation, or data-intensive software engineering, ideally with 5+ years of experience in a financial, investment, or technology-driven environment.
• Deep experience building production-grade data pipelines, including ingestion, transformation, validation, orchestration, monitoring, and deployment.
• Strong Python programming skills, with relevant experience working with Dagster, Airflow or similar technologies.
• Experience with modern data architecture patterns such as data lakehouse, Medallion architecture, composable data systems, microservices, and event-driven or workflow-oriented architectures.
• Familiarity with Data Mesh concepts, including decentralized data ownership, domain-oriented data products, governance, and discoverability.
• Experience with orchestration, workflow, and data transformation tools such as dbt, Polars, Pandas, Apache Arrow, or comparable technologies.
• Practical experience using AI-assisted development tools such as Claude, ChatGPT, GitHub Copilot, or similar platforms to support data pipeline development, automation, testing, documentation, and engineering productivity.
• Demonstrated ability to mentor engineers, lead technical workstreams, and influence engineering practices across a team.
• A strong sense of ownership and the ability to operate effectively in ambiguous environments, balancing tactical delivery with long-term architectural thinking.
• A passion for building systems that are efficient, scalable, reliable, observable, and easy for others to use.
• An understanding of how data infrastructure supports the broader investment process, and a desire to deliver solutions that improve outcomes for clients and create meaningful business impact.

The base salary range for this role is $175,000 – $200,000 per year. Actual compensation will be determined based on a candidate’s skills, qualifications, and relevant experience. In addition to base pay, this position may be eligible for discretionary incentive compensation and includes participation in Acadian’s comprehensive benefits program, which includes health, retirement, and wellness offerings.

About the Role
Our Platform Infrastructure team is the backbone of everything we do at Attentive, providing a resilient and cost-effective platform that seamlessly handles billions of events from over 100 million customers daily. We own everything from compute, persistence, and networking to observability and deployments. Joining our team offers a high-growth career opportunity to collaborate with some of the world’s most talented engineers in a high-performance, high-impact culture.

What You’ll Accomplish

• Spearhead FinOps initiatives to increase cost transparency and optimize resource utilization across teams
• Provide guidance and mentorship to engineers on cost-optimization best practices
• Collaborate with teams across the organization to implement cost-saving measures
• Analyze, troubleshoot, coordinate, and resolve complex infrastructure issues
• Proactively lead infrastructure initiatives that have a company-wide impact
• Partner with engineering teams to influence cost-effective architectural and design choices
• Develop automation workflows to enhance team productivity and efficiency
• Foster a culture of continuous improvement by encouraging innovative thinking and challenging established norms

Your Expertise

• Bachelor's degree in Computer Science, Engineering, or related field; Master’s degree preferred
• 2+ years of experience in FinOps or cloud cost management
• 5+ years of experience in cloud infrastructure management, development or related roles
• Proficiency in some of the following technologies: AWS, Datadog, Kubernetes, Vantage, Terraform, Java
• Strong analytical and problem-solving skills with a keen attention to detail
• Excellent communication and leadership abilities
• Ability to work collaboratively in a cross-functional team environment

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $180,000 - $240,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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About the Role
We’re looking for a highly driven Senior Software Engineer to join our Streaming team, which powers the backbone of Attentive’s messaging and personalization platform. Our event streaming systems handle over 2 million messages per second and sit at the heart of how product and data engineering teams build real-time, customer-facing experiences.

What You’ll Accomplish

• Architect and evolve Attentive’s next-generation event streaming platform: Design high-throughput, low-latency solutions that power mission-critical messaging, personalization, and data integration use cases across Attentive’s ecosystem
• Enhance self-service for product engineering and data teams: Build and refine self-serve tools for event observability, debugging, load testing, and system configuration, empowering teams to experiment and ship quickly
• Simplify and modernize streaming architecture: Remove unnecessary abstraction layers, enable direct access for power users, and ensure the platform is flexible for both “paved path” and advanced use cases
• Solve complex distributed systems challenges: Improve event delivery reliability, cost efficiency, and system integration for real-time and batch workloads
• Champion best practices and technology selection: Stay ahead of industry advancements in event streaming, advocating for tools and approaches that balance innovation with long-term reliability
• Collaborate across engineering: Partner with product, data, and infrastructure teams to launch new customer-facing features, integrations, and scalable solutions built on streaming infrastructure

Your Expertise

• 5+ years experience architecting and supporting high-throughput, distributed systems at scale—especially those involving event streaming or messaging platforms
• Deep understanding of the internals of distributed streaming frameworks such as Kafka, Flink, Pulsar, and/or Spark
• Proficient in Java (Spring Boot) and familiar with modern development practices, including object-oriented design, data structures, and algorithms
• Able to debug issues across the stack—from message serialization and event schemas to network and JVM tuning—and communicate tradeoffs clearly
• Familiar with resource scheduling, data locality, and how infrastructure choices impact cost and system behavior
• Experience with observability and developer tooling for streaming (e.g., tracing, metrics, replay).Infrastructure-as-code expertise (Terraform, Helm), comfortable with Kubernetes (EKS) and cloud-native environments
• Track record of modernizing platforms: sunsetting legacy systems, moving to managed services, or implementing self-service capabilities
• Excited by new technologies, but pragmatic about introducing them—focused on solving real business problems

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $150,000-$210,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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About the Role

Our Engineering team creates innovative product experiences that power personalized marketing at massive scale. We develop cutting-edge applications and systems that process 100s of billions of messages and events per year, enabling marketers to connect effectively with hundreds of millions of consumers. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented engineers in a high-performance and high-impact culture.

As a Senior Software Engineer in our Intelligent Messaging, you will pioneer the future of personalized 1:1 marketing by architecting robust, scalable backend systems powered by advanced AI and LLMs, including cutting-edge Generative AI and GPT technologies. Collaborating with top-tier engineers, data scientists, product managers, and designers, you’ll craft the foundation and reshape the platform of multi-channel messaging experimentation to support innovative, AI-driven applications that empower marketers to forge deep, meaningful connections with consumers at scale. Your impactful work will drive the delivery of billions of tailored messages, transforming consumer shopping experiences and fueling success for the world’s leading brands.

What You’ll Accomplish

• Develop and maintain scalable backend systems for our customer-facing products, ensuring high performance and reliability.
• Collaborate with cross-functional teams to build applications that support multi-channel communications for marketers.
• Implement and optimize systems that process and deliver billions of messages daily.
• Improve code quality through code reviews, testing, and advocating for best practices.
• Identify and address technical debt to ensure the long-term health of our codebase.
• Drive architectural design and technical decisions, and stay current with emerging technologies to enhance our products.

Your Expertise

• 5+ years of professional experience in software development focusing on backend systems.
• Proficiency in Java, Python, or Go, with a strong understanding of object-oriented programming.
• Experience building and maintaining scalable, high-performance applications.
• Proven ability to collaborate effectively with cross-functional teams.
• Solid understanding of software development best practices, including code reviews, writing tests, and continuous integration.

Nice to Haves

• Experience with service-oriented architecture and distributed systems.
• Familiarity with AWS services and cloud infrastructure.
• Knowledge of databases such as DynamoDB, Postgres, or Redis.
• Experience with messaging systems or streaming platforms (e.g., Kafka, Pulsar).
• Familiarity with frontend development with React and TypeScript.
• Experience with DevOps practices and tools such as Docker and Kubernetes.

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS.
• Infrastructure tooling includes Istio, Datadog,Terraform, CloudFlare, and Helm.
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Kinesis, AirFlow, Postgres, Planetscale, and Redis, hosted via AWS.
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and PlaywrightOur automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $190,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Staff Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

• This leader will own the multi-year strategy, roadmap, and execution across the ads supply ecosystem:
  • Supply Exchange & Inventory Integrations: Drive Moloco’s OpenRTB integrations with top-tier third-party supply partners and exchanges, expanding Moloco’s access to high-quality, global, multi-format inventory across gaming and non-gaming verticals.
  • Lead Moloco’s end-to-end General Supply strategy, including Exchange integrations, OpenRTB supply diversification, publisher onboarding, and supply ecosystem expansion.
  • Define, evangelize, and deliver a multi-year supply vision that improves supply quality, scalability, integration reliability, and long-term differentiation
• Conducting deep-dive analysis and experiments to influence product decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Preferred Qualifications:

• Advanced degree. PhD is highly desirable. 
• Deep expertise in the programmatic supply ecosystem, including ad exchanges, SSPs, OpenRTB protocols, auction mechanics, and cross-platform integration
• Demonstrated ability to drive cross-org alignment, influence senior stakeholders (Directors/VPs), and execute through large engineering teams
• Familiarity with publisher ad servers, targeting logic, and impression delivery workflows
• Deep knowledge of supply-side performance metrics such as fill rate, eCPM, latency, bid density, impression opportunities, and unique users—and how to optimize for them
• Hands-on experience with integrations and partner-facing APIs, including defining requirements for interoperability with DSPs, exchanges, ad networks, DMPs, and other adtech partners

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Senior Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Evaluating ads integrity: understanding changes and drivers of our complex systems, diagnosing fraud claims and mitigating fraud escalations through a set of input/output metrics of each component.
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Economics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Data Scientist II, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, ML) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers
• Evaluating ads system health: understanding changes and drivers of our complex systems, and diagnosing issues through a set of input/output metrics of each component.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Provide strategic thought partnership to cross-functional teams, leveraging data-driven insights to influence and guide product decisions, roadmap prioritization, and overall business strategy.
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with Product Management, Engineering stakeholders ;work effectively with cross-functional partners in a global company.
• 3+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.
• Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

Position Overview

We are seeking a Senior RAN System Architect to lead the definition, integration, optimization, and product roadmap execution of LTE/5G radio systems across our global satellite-ground infrastructure—the first and only space-based cellular broadband network accessible directly by standard mobile phones.

This role sits at the intersection of beamforming, fronthaul design, scheduler behavior, and interference management, while also owning the translation of system capabilities into a coherent product roadmap and serving as a trusted technical interface to customers and partners.

The ideal candidate brings deep experience from a leading RAN vendor, a strong understanding of baseband design and scheduling pipelines, and the ability to bridge engineering realities with customer expectations in a fast-moving, non-traditional deployment environment.

Key Responsibilities

• Lead end-to-end RAN performance optimization by analyzing and tuning eNB/gNB behavior to maximize cell throughput (TpT), coverage, reliability, and interference efficiency.
• Ensure robust operation of terrestrial RAN features—such as scheduling, MIMO, mobility, and interference coordination—when deployed over AST's space-based infrastructure via standard CPRI/eCPRI interfaces.
• Own cell- and network-level performance modeling, including:
  • Spectral efficiency
  • Cell density and reuse strategies
  • Beam transitions and UE tracking
  • Interference prediction and mitigation
• Own the RAN feature roadmap: define, prioritize, and sequence feature delivery in collaboration with product management and engineering leads, balancing technical feasibility, development complexity, and commercial commitments.
• Drive feature provisioning end-to-end—from requirements definition and vendor engagement through integration, validation, and controlled enablement across the network—ensuring new capabilities are introduced reliably and without degrading existing performance.
• Manage customer and partner expectations by translating complex system constraints and development timelines into clear, honest, and actionable communications; serve as the primary technical point of contact for feature-related inquiries from operators, partners, and key stakeholders.
• Maintain a living capability roadmap that honestly reflects the gap between customer-expected functionality and current system state and defines a credible path—with milestones and dependencies—to close that gap.
• Collaborate with system integration, DSP, RF, and core network teams to align baseband behavior with AST's product goals.
• Define test strategies and validation plans that ensure system-wide performance across the satellite, ground, and RAN layers.
• Serve as a key technical interface to RAN vendors and partners, participating in debugging, integration workshops, and roadmap alignment.

Qualifications

Education:

• BSc or MSc in Electrical Engineering, Communications Engineering, or related field from a recognized institution.
• Relevant certifications in cellular systems or wireless communications (e.g., 3GPP, LTE/5G) are a plus.

Experience:

• A minimum of 8–12 years in cellular system engineering, RAN performance, or architecture roles (including vendor-side experience).
• Proven experience in real cellular network deployment and optimization (lab and field).
• Expertise in 3GPP specifications for 4G and 5G, with hands-on interpretation and application to system design.
• Firm understanding of PHY/MAC/RLC/PDCP/RRC layers and their interplay in baseband systems.
• Demonstrated experience owning or co-owning a technical product roadmap, including prioritization under uncertainty and communication of trade-offs to non-engineering stakeholders.

Preferred Qualifications:

• Experience with non-terrestrial networks (NTN) or space-ground hybrid architecture.
• Hands-on background with beamforming systems, antenna arrays, and RF front-end constraints.
• Familiarity with traffic modeling, scheduler design, and spectral efficiency optimization at scale.
• Experience working with RAN vendors (e.g., integration, debugging, feature enablement).
• Knowledge of fronthaul protocols (CPRI/eCPRI) and transport considerations in constrained or high-latency environments.
• Background in predictive modeling, data science, or simulation frameworks for network planning.
• Exposure to O-RAN architectures and vendor interoperability.
• Experience interfacing directly with MNO customers or enterprise partners on capability delivery, timeline commitments, or technical pre-sales engagements.

Soft Skills

• Strong interpersonal skills with the ability to lead cross-functional technical discussions (DSP, RF, Systems, Core).
• Proven ability to collaborate effectively within distributed, multidisciplinary teams.
• Excellent written and verbal communication skills; able to distill complex concepts for technical and executive audiences.
• Comfortable delivering difficult messages—whether to customers facing delayed features or to internal teams pushing back on unrealistic commitments—with clarity, data, and constructive alternatives.
• Skilled at roadmap storytelling: able to frame development trade-offs and sequencing logic in a way that builds confidence with operators, partners, and leadership.
• Meticulous attention to detail to ensure the accuracy of models, documentation, and deliverables.
• Analytical problem solver with a bias toward measurable outcomes and system-wide impact.
• Ownership mindset; comfortable navigating ambiguity in cutting-edge, non-traditional deployments.

Technology Stack

• RAN & Baseband: eNB/gNB stacks, scheduler frameworks, MIMO/beamforming, HARQ, CQI/PMI/RI, mobility and ICIC/eICIC/CoMP.
• Interfaces & Transport: CPRI/eCPRI, O-RAN interfaces, Ethernet/IP transport, timing/synchronization (PTP, GPS).
• Modeling & Simulation: MATLAB, Python, NumPy/Pandas, simulation tools for link/system-level performance.
• Data & Visualization: Jupyter, data pipelines for KPI analysis; familiarity with logging/telemetry systems.
• Product & Roadmap Tools: familiarity with roadmap management frameworks (e.g., Jira, Confluence, or equivalent) and structured feature tracking practices.
• Standards & Specs: 3GPP (LTE/NR), NTN-related specs, vendor roadmaps and interoperability frameworks.

Physical Requirements

• Ability to work in a standard office environment and use a computer for extended periods.
• Ability to participate in lab testing environments with standard RF and baseband equipment.
• May require occasional travel for integration workshops, vendor engagements, customer visits, or field validations.

This job description may not be inclusive to the duties and responsibilities listed. Additional tasks may be assigned to the employee from time to time or the scope of the job may change as needed by business demands. 

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 mid-level Software Engineer with a strong background in optimization to join our growing team at Anduril Labs. In this role, you will be instrumental in developing advanced algorithms and software solutions to tackle complex, multi-domain optimization problems critical to national defense and Anduril’s autonomous systems.

The ideal candidate possesses deep expertise in classical optimization algorithms, robust Python programming skills, and a solid foundation in data modeling. Experience with developing hybrid quantum optimization solutions is a plus. You will leverage state-of-the-art, GenAI-powered development tools such as Claude Code to accelerate solution development and enhance our optimization software. This role demands creative problem-solving, a self-starter mentality, and the ability to rapidly apply algorithmic theory and mathematic modeling to practical, real-world optimization challenges. You will be designing, implementing, and deploying optimization algorithms and services that integrate seamlessly into larger defense systems, working across various platforms (on-prem, cloud, and hybrid quantum computing environments). Familiarity with modeling linear and non-linear optimization problems, rapid prototyping, integrating optimization solutions into existing architectures, leveraging APIs, and utilizing open-source tools will be crucial.

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

• Design, develop, and implement highly efficient optimization algorithms and software solutions to solve challenging problems in areas such as resource allocation, scheduling, routing, mission planning, control systems, and supply chain logistics.
• Apply classical optimization techniques (e.g., linear programming, mixed-integer linear programming, combinatorial optimization, network flow, dynamic programming, heuristics, metaheuristics) to model and explore novel approaches.
• Utilize GenAI tools (e.g., OpenAI Codes, Claude Code, GitHub Copilot) to rapidly prototype, refine, and test algorithmic solutions, improving development velocity and code quality.
• Develop robust data models and efficient data pipelines to support complex optimization problems, ensuring data integrity and efficient processing for algorithmic inputs and outputs.
• Collaborate with multidisciplinary teams (software engineers, data scientists, domain experts, product managers) to integrate optimization engines and services into larger defense systems and platforms.
• Perform rigorous testing, validation, and performance analysis of optimization solutions, ensuring scalability, reliability, and accuracy under diverse operational conditions.
• Participate actively in the entire Software Development Lifecycle (SDLC) from requirements gathering and design to deployment, monitoring, and maintenance.
• Support Anduril- and customer-funded R&D efforts, contributing to technical documentation, presentations, and patent applications.

REQUIRED QUALIFICATIONS

• Bachelor's degree in Computer Science, Software Engineering, Applied Mathematics, Operations Research, or a related quantitative field.
• 3+ years of professional experience in software development with a dedicated focus on optimization, algorithmic problem-solving, or operations research.
• Experience solving optimization problems in defense, transportation, supply chain, logistics, network optimization, smart grids or similar
• Expert proficiency in Python for scientific computing and robust software development.
• Strong theoretical and practical understanding of classical optimization algorithms (e.g., linear programming, mixed-integer linear programming, constraint programming, network flow, dynamic programming, heuristics, meta heuristics).
• Hands-on experience with optimization libraries and commercial/open-source solvers (e.g., SciPy Optimize, PuLP, CVXPY, Gurobi, CPLEX, OR-Tools, GEKKO). Experience with Gurobi is a plus.
• Solid experience with data modeling, data structures, and algorithms to efficiently prepare, process, and manage data for optimization problems.
• 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.
• Proficiency in using numerical computing libraries such as NumPy, SciPy, and Pandas.
• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.
• Ability to develop, test, and deploy software effectively on Linux-based systems.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance.
• Experience with Git version control, build tools, and CI/CD pipelines.
• 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.

PREFERRED QUALIFICATIONS

• • Master's or Ph.D. in Computer Science, Applied Mathematics, Operations Research, or a closely related quantitative field.
  • Familiarity with or a strong interest in quantum optimization algorithms, quantum computing concepts, or quantum-inspired heuristic approaches. Experience with D-Wave’s quantum annealing platform is a plus.
  • Experience with performance-critical programming languages such as C++ or Java.
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying scalable optimization solutions or high-performance computing (HPC) environments.
  • Prior experience in defense, aerospace, logistics, supply chain management, robotics, or manufacturing optimization domains.
  • Familiarity with integrating machine learning models with optimization techniques (e.g., prescriptive analytics, reinforcement learning for optimization).
  • Excellent communication skills with the ability to articulate complex technical concepts, present findings, and influence technical direction across diverse teams.
  • 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. 

Director, Operations & Implementation 
 

Location: Huntsville, AL 

Work Environment: On-Site 
 

Role Summary: 
 

Exiger is seeking a Director of Operations & Implementation to stand up and run the operational backbone of a highly strategic, federally aligned supply chain resilience program. Reporting into program leadership, this individual will own the execution of Red Team / Blue Team workflows, data onboarding, and action management within a live control‑tower environment. This is a highly visible, mission‑critical role operating at the intersection of national security priorities, advanced data and AI capabilities, and real-time operational execution—requiring strong leadership, technical fluency, and the ability to deliver under compressed timelines. 
 

What You’ll Do: 
 

• Lead the operational execution of Red Team (supply chain vulnerability analysis) and Blue Team (mitigation and optimization) workflows across the program 

• Design and manage end-to-end data onboarding processes, including intake, validation, prioritization, and integration into the Command Center environment 

• Establish and drive the operational cadence for control-tower activities, including recurring analysis cycles, action tracking, and executive reporting 

• Partner closely with engineering, data science, and product teams to translate operational requirements into scalable workflows and system capabilities 

• Oversee action management processes, ensuring insights are converted into clear, trackable, and outcome-driven initiatives 

• Coordinate across federal stakeholders, internal teams, and advisors to ensure alignment on priorities, timelines, and deliverables 

• Identify operational gaps and continuously improve processes to support rapid scaling and evolving mission requirements 
   

What You Need: 
 

• Strong experience leading complex operational programs, ideally within federal, defense, intelligence, or highly regulated environments 

• Working knowledge of data engineering and analytics tooling, including Python (e.g., Pandas), SQL, and modern AI/ML frameworks, with the ability to guide technical teams, evaluate data workflows, and translate business requirements into scalable data solutions 

• Proven ability to stand up and manage cross-functional workflows involving data, engineering, and analytics teams 

• Experience working with large-scale data onboarding, integration, or analytics-driven in an operations center environment 

• Excellent communication and stakeholder management skills, with the ability to operate effectively with senior leadership and government counterparts 

• Strong organizational and execution skills, with the ability to manage multiple workstreams in parallel under tight timelines 

• Ability to translate ambiguous, evolving requirements into structured processes and actionable plans 

• Must be a U.S. Citizen with an active Top Secret security clearance and eligibility for Sensitive Compartmented Information (SCI) 

Professional Experience Required: 
 

• 8+ years of experience in operations, implementation, program management, or a related field 

• Experience working in or supporting federal programs, defense, intelligence, or national security initiatives is strongly preferred 

• Background in supply chain, risk management, analytics, or data-driven operational environments is a plus 

• Experience working in fast-paced, high-growth, or mission-driven organizations 
   

Why Exiger: 
 

Exiger is transforming how governments understand and manage supply chain and software risk. This role offers a rare opportunity to: 
 

• Help stand up and operate a mission-critical control-tower capability supporting national security priorities 

• Work directly with senior federal stakeholders, including DoD and defense industrial base partners 

• Build and scale operational processes that will define how supply chain resilience is managed at a national level 

• Operate at the intersection of technology, data, and mission execution in a highly visible program 
   

Why You’ll Love Working at Exiger: 
 

• High-performance culture rooted in accountability, collaboration, and a shared commitment to excellence. 

• Discretionary Time Off for all employees, with no maximum limits on time off 

• Industry leading health, vision, and dental benefits 

• Competitive compensation package 

• 16 weeks of fully paid parental leave 

• Flexible, hybrid approach to working from home and in the office where applicable 

• Focus on wellness and employee health through stipends and dedicated wellness programming 

• Purposeful career development programs with reimbursement provided for educational certifications 
   

#Li-Hybrid

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed! 

Responsibilities

• Contribute directly to impactful improvements to HRT’s low-latency trading systems
• Analyze large datasets to understand how complex systems and networks behave in real-world conditions, such as exchange technology and performance of HRT systems
• Build Python-based tools and scripts to collect, clean, and visualize data in a clear and actionable way
• Design and run experiments to measure the impact of changes and identify opportunities for improvement
• Collaborate closely with HRT’s Algorithm Development, Trading Technology, and Business Development teams to discover, research, and implement improvements to HRT’s architecture
• Liaise with exchanges globally to better understand their technology and stay up to date on changes and improvements

Qualifications

• A technical degree or equivalent practical experience
• Experience with Python and Pandas 
• Proficiency in data analytics including statistics, data visualization, and working with large data sets
• Strong curiosity about how financial systems, networks, and cutting-edge technology work, and a willingness to learn new concepts quickly
• Ability to think analytically, ask insightful questions, and approach unfamiliar problems methodically
• Strong cross-functional communication skills and an interest in collaborating with others

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is a quantitative trading firm at the forefront of technological innovation. We build and deploy cutting-edge systems within one of the world’s most advanced computing environments to power our global trading operations. Our non-siloed, collaborative coding environment empowers talented engineers to make significant contributions and see their impact daily. At HRT, you'll be challenged to solve the most complex problems in trading alongside many of the brightest minds in the field.

We are seeking highly motivated and skilled Research Engineers who will work very closely with our Algo Developer (Quant Research) trading teams. These roles require exceptional programming fundamentals, a strong user focus, and the ability to thrive in a fast-paced environment with constantly evolving requirements. Multitasking and context switching are inherent aspects of this role, through which you will gain insight into the ideation and execution of some of the world's most sophisticated trading strategies.  

Research Engineers at HRT work on a wide variety of projects. Examples include:

• Designing highly customized quantitative systems that enable Algo Developers to easily express and backtest new predictive signals.
• Building world-class research tooling to speed up Algo Developers’ research iteration.
• Aiding the development and deployment of very large deep learning models for HRT’s live trading.
• Improving HRT’s monetization systems which turn our predictions into profitable trades.
• Evaluating sim vs. live differences to improve the fidelity of our simulations.
• Building systems to monitor and manage live trading.
• Specializing in specific time horizons, from high frequency trading to mid-to-low frequency hedge fund-style strategies.
• Working across a very wide variety of asset classes (from equities to fixed income to options) and regions (from North America to Asia Pacific) – you’ll interact with markets across the world!

Responsibilities

• Design, develop, and maintain robust, performant, and scalable software systems.
• Optimize existing codebases for performance, reliability, and efficiency.
• Debug complex issues across distributed systems in a time-sensitive environment.
• Optimize both the mechanics and ergonomics of Algo Developer research workflows; this requires developing a deep intuition for research methodologies.
• Balance the short term goals of individual trading teams with the longer term goals of HRT’s generalized trading platforms across trading teams. Because we don’t work in a pod environment, REs on different trading teams are expected to share technology and ideas.

Qualifications

• Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. If you are currently pursuing your Bachelor's degree, please apply to our Campus/New Grad opportunities.
• Previous experience at a top-tier finance or technology company with an excellent track record of rapid advancement and superlative reviews.
• Experience with supporting internal users is preferred; bonus if you have real hands-on experience with quant research and/or ML/Deep Learning platforms.
• Experience with python numerical, ML and data-oriented libraries is a big plus (e.g. pandas, scikit, pytorch, etc.)
• Candidates should be prepared for technical interviews in either Python or C++. While there is no hard language requirement for RE roles, proficiency in one of these languages will be assessed during the interview process.
• Kindness and empathy is a real requirement. No “smart jerks” at HRT. 
• Strong understanding of data structures, algorithms, and design principles.
• Excellent communication skills, both written and verbal.
• HRT ships every day. The ability to thoughtfully, methodically, and reliably deploy new software and features is a critical skill. 
• If you have management experience, that’s always a bonus – but even so, expect to code!

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

For more info about interviewing at HRT, see this blog!

Hudson River Trading (HRT) is seeking curious, thoughtful engineers who enjoy working with data and solving real-world technical problems to join our growing Market Structure Analysis team. In this role as a Quantitative Latency Engineer, you’ll apply data-driven methodologies to understand and optimize trading technology and real-time interactions with financial markets across the globe, spanning traditional and crypto exchanges. No prior finance experience is needed!

Responsibilities 

• Analyze time series network and exchange protocol captures
• Become familiar with the details of specific markets, attend presentations and liaise with exchange counterparts
• Research exchange features, capabilities, and architecture
• Automate collection and visualization of metrics that quantify efficacy of exchange communication
• Formulate and conduct controlled experiments that measure impact of calculated changes to HRT’s trading infrastructure
• Communicate ideas, requirements, and results across disparate teams
• Improve fill rate of our hardware-based trading strategy
• Reduce incidence of cancel-reject responses
• Investigate and report details of various latency-sensitive exchanges

Profile 

• You possess a degree in Data Analytics or a related field
• You can collect and interpret network and/or financial market data
• You have professional experience in latency reduction, preferably in finance
• You have a basic understanding of proprietary trading and exchange technologies

Skills 

• Proficiency in data analytics including statistics, data visualization, and working with large data sets
• Basic understanding of TCP and UDP network protocols
• Extensive experience with Python and relevant data libraries (Pandas, Numpy/Scipy)
• Some familiarity with the details of modern computer systems and networks
• Experience with real time exchange market data and order entry a plus

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Hudson River Trading (HRT) is seeking exceptional full-time PhD students to join our Algorithm Development team. Algorithm Developers are responsible for building and maintaining the models that drive our trading. A typical day involves applying rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models. 

In this role, you will work alongside fellow Algorithm Developers and Software Engineers to research, develop, and test novel order execution and model training methods to increase trading efficiency. This will involve running models live on our high-performance trading infrastructure and analyzing daily performance to maintain ongoing profitability. You can expect to apply your advanced academic research experience and expertise to impactful real world problems in trading across time horizons and machine learning strategies.

Profile

• You’re excited to apply your research expertise to identify new opportunities in worldwide markets  
• You enjoy both self-guided research and collaborating with others to analyze and fix problems efficiently
• You are a critical thinker who can learn and implement new skills in a fast-changing environment

Qualifications

• You are a full-time PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2026
• Fluency in Python
• Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
• Brilliant analytical and problem-solving skills
• Ability to work creatively and independently on long-term technical problems

The estimated base salary for this position is 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Role

We are looking for a Staff Machine Learning Engineer to help us build a best in class ML Ecosystem to advance our product suite with clinical AI. The ideal candidate works exceptionally well across disciplines and delivers high quality outcomes continuously, with a relentless focus on reliable systems and developer experience.

**This role is fully remote within the US**

What You’ll Do

• Build and scale machine-learning driven features across multiple products
• Design reusable architecture that powers and accelerates machine learning development across the company
• Set the standard for development and ML practices at SmarterDx and mentor other engineers

What You Bring

• You Bring

  • 10+ years of development experience with a focus on Machine Learning and Engineering roles
  • Strong proficiency in Python and SQL, with experience in machine learning libraries (Pytorch, Tensorflow)
  • Experience with managing the full model production lifecycle, including deployment, release, and post-launch monitoring
  • Experience working with a diverse, cross-disciplinary team to integrate machine learning into product features
  • Experience with cloud platforms (preferably AWS) and their machine learning services.
  • Experience project managing a small team using a modern agile methodology
  • Experiencing influencing a cross-disciplinary organization to adopt best practices
  • Strong understanding of data engineering and architecture principles.
  • Excellent collaboration and communication skills, with a passion for solving challenging problems in a team environment.

Nice To Haves

• You're a former startup founder, or have been the first engineering hire at a startup
• Experience in the health tech domain, particularly in hospital billing systems
• Experience with end-to-end machine learning project lifecycle, from data collection and model training to deployment and monitoring.
• Deployment of LLM systems into Production environments.
• Contributions to open-source projects or active participation in the machine learning community.

Our Tech Stack

• Python, PyTorch, pandas/Polars, Airflow, Snowflake, dbt, AWS, MLflow, Sagemaker, Terraform, K8s

Compensation

$230-260k base salary

#LI-Remote

Senior Data Analyst – Blue Team (Supply Chain Risk & Mitigation) 

Location: Huntsville, Alabama (Customer Site with Remote Flexibility) 

Work Environment: Hybrid / On-Site as required 

Role Summary: 

Exiger is seeking Data Analysts to join our Blue Team supporting a high-impact Department of Defense–aligned supply chain risk management program. In this role, you will focus on the defensive side of supply chain risk—developing mitigation strategies, identifying alternate sourcing pathways, and delivering actionable recommendations that government decision-makers can execute. Reporting to the Director of Operations & Implementation, you will play a key role in strengthening mission readiness through data-driven insights and operational planning. 

What You’ll Do: 

• Illuminate supply chains using proprietary and government-furnished data 

• Produce recurring risk mitigation decision-support products 

• Conduct alternate sourcing analysis for at-risk suppliers and components 

• Develop mitigation plans with timelines, owners, and closure criteria 

• Execute data quality validation workflows and identify anomalies 

• Develop data quality scorecards and remediation recommendations 

• Support Course of Action (COA) development with cost and timeline analysis 

• Track mitigation actions and maintain program status logs 

• Prepare materials for executive briefings and control tower sessions 

• Coordinate with government stakeholders on data and sourcing validation 

• Support onboarding and enrichment of new data sources 

• Maintain SOPs and support team onboarding 

What You Need: 

• Strong analytical mindset and ability to translate data into decisions 

• Proficiency in Excel, Python (pandas), SQL, or similar tools 

• Experience producing reports or briefings for stakeholders 

• Familiarity with supply chain mitigation and sourcing strategies 

• Strong written communication and attention to detail 

• Ability to meet production deadlines in a team environment 

Professional Experience Required: 

• 3+ years in data analysis, supply chain, logistics, or intelligence 

• Experience with structured research and documentation 

• Background analyzing complex systems or datasets 

• Experience in government, defense, or regulated environments 

• Active TS/SCI clearance (required) 

Preferred Qualifications: 

• Experience with defense logistics or acquisition programs 

• Familiarity with CAGE, NSN, or defense data taxonomies 

• Experience with Tableau, Power BI, or visualization tools 

• Experience with data governance or master data management 

• Familiarity with tools like Jira or Confluence 

Why Exiger: 

Exiger is transforming how governments understand and manage supply chain risk. In this role, you will support mission-critical programs, work alongside experts in AI and risk analytics, and deliver insights that directly impact national security decision-making. 

Why You’ll Love Working at Exiger: 

• High-performance culture rooted in accountability, collaboration, and a shared commitment to excellence 

• Discretionary Time Off with no maximum limits 

• Industry-leading health, vision, and dental benefits 

• Competitive compensation package 

• 16 weeks of fully paid parental leave 

• Flexible, hybrid approach to working 

• Wellness stipends and employee health programming 

• Career development support and certification reimbursement 

#Li-Hybrid 

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.

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking an Insights & Integrations Consultancy Data Scientist who will be responsible for transforming complex data into clear, business-impactful insights that drive portfolio expansion, retention, and real-world outcomes for fleet operators around the world. This role sits at the intersection of data science, customer consultancy, and sustainability — where your ability to communicate the why behind the data matters as much as the analysis itself. If you love turning data into decisions and have a passion for sustainability and clean transportation — we would love to hear from you!

What you'll do:

As an Insights & Integrations Consultancy Data Scientist, your key area of responsibility will be partnering with strategic accounts to drive ecosystem expansion and retention — not just through technical analysis, but by translating that analysis into business impact that resonates with fleet managers, executives, and non-technical stakeholders. You will develop and maintain deep expertise across the Geotab platform, engaging directly with partners and end-users to optimize their use of Geotab's technology, presenting data-driven insights in ways that clearly demonstrate ROI, cost savings, and efficiency gains. Day-to-day, you will design and deliver Big Data dashboards and analytics tools, maintain Airflow pipelines for continual data analysis using SQL and Python, develop proof of concepts, and solve complex business problems through customer-tailored algorithms and predictive models. You will also represent Geotab as a thought leader at industry events and trade shows — particularly in the areas of fleet electrification and sustainability — and travel quarterly to Canada for team meetings, with additional on-sites at key strategic accounts.

You will work closely with Account and Engagement Managers within Geotab's Sales Channels, the Signature Accounts Team, Product Management, and Solutions Engineering — relationships that are essential to identifying growth opportunities and translating customer feedback into product improvements. To thrive in this role, you will bring an exceptional ability to communicate complex technical concepts to non-technical audiences, a consultative mindset focused on business outcomes over technical jargon, and a genuine passion for sustainability and the electrification of commercial fleets.

How you'll make an impact:

• Develop and maintain comprehensive knowledge of the Geotab ecosystem, serving as a Subject Matter Expert (SME) to empower end-users and partners and enhance their understanding of Geotab solutions.

• Engage and collaborate with partners and end-users to optimize their utilization of Geotab's technology, products, and solutions, tailoring the approach to meet their specific needs.

• Contribute to the continuous improvement of the company's offerings by providing partner and end-user feedback, providing opportunities to collaborate with Product Management teams.

• Create and optimize data-driven dashboards for cross-functional use, facilitating informed decision-making and efficient collaboration with a focus on expansion and retention of existing customers.

• Ensure partner and end-user satisfaction through prompt and accurate service, bolstering internal team support by providing additional insights and know-how.

• Collaborate with the Geotab revenue generating teams to identify and deliver effective solutions for customer challenges, by working closely with them and their partners, contributing to sales growth, ecosystem expansion and customer retention.

• Support Geotab's partner upskilling, driving them towards excellence to support customers across unique channels, using best practices, and leveraging a deep understanding of industry verticals.

• May be involved in developing and implementing proof of concepts. This involves creating a small-scale version of the solution to demonstrate its feasibility and effectiveness in the customer's environment.

• Staying updated with industry trends, competitor products, and market demands is crucial. Need to understand the broader landscape in which Geotab operates to position their solutions effectively.

• Keep accurate records of customer interactions, solution designs, and outcomes is important. This helps in creating case studies, improving processes, and maintaining a repository of successful solutions for reference.

• Deliver compelling technical presentations and demonstrations to customers. They showcase the features and benefits of the product or service, highlighting how it solves the customer's problems.

• Work closely with the sales team and fellow engineers throughout the sales cycle as needed. Provide technical support, answer technical questions, and address concerns that potential customers may have in regards to their area of subject matter expertise.

• Based on customer requirements, design customized solutions or configurations using the company's products. They create proposals and presentations that outline how the solution meets the customer's needs, often through demonstrations or prototypes.

• Even before a sale is made, may assist with technical inquiries from potential customers. This could involve explaining technical details, providing documentation, or guiding customers on how to integrate the solution into their existing systems when expertise beyond the general area is required.

• Solve complex business problems by providing analytics or analytics-based consulting, including customer-tailored algorithms and predictive models, under guidance or mentorship.

• Maintain airflow pipelines for continual data analysis combining SQL queries and python scripts.

• Design, maintain and deliver Big Data dashboards and tools; document stakeholder requirements, resolve issues, and fulfill change requests.

What you'll bring to this role:

• Bachelor's degree in Engineering, Computer Science, Information Technology, or a related field; equivalent combination of education and/or work experience may be substituted.

• 3–5 years of experience in a relevant customer-facing technical role, including Solutions Engineering, Sales Engineering, Integration Engineering, Engineering Support, Software Development, Data Science, or Technical Account Management.

• 1–3 years of hands-on experience with SQL (Google BigQuery preferred) and data science tools (Python, pandas, numpy preferred).

• Experience working with large data environments and demonstrated ability to extract value from very large datasets, including data modeling and data warehouse concepts.

• Data visualization skills, particularly in dashboarding platforms such as Power BI or Tableau.

• Technical knowledge of telematics, IoT, APIs, and related technologies; working knowledge of hardware integrations is a bonus.

• Strong communication and presentation skills, with the ability to articulate complex concepts to both technical and non-technical audiences, and to collaborate effectively across cross-functional teams.

• Effective problem-solving and critical thinking abilities, with the capacity to assess customer challenges and propose viable solutions.

• A customer-focused mindset with strong time management and organizational skills; able to manage multiple projects and priorities simultaneously.

• Desire to stay current with emerging technology and the flexibility to adapt to growing market demands.

• Ability to travel up to 20% of the time internationally; valid passport required.

Why job seekers choose Geotab:

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This position is based in our Tempe, Arizona office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This is a remote position, open to candidates who reside in: Dallas, Texas. You will be fully remote; however, our approach to work may adapt over time. Future models could potentially involve a hybrid presence at the hub office associated with your metro area. #LI-Remote

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $101,844 - $133,670 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This is a remote position, open to candidates who reside in: Atlanta, Georgia. You will be fully remote; however, our approach to work may adapt over time. Future models could potentially involve a hybrid presence at the hub office associated with your metro area. #LI-Remote

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

Who You Are

As a Data Scientist on this team, you are the "bridge" between raw infrastructure telemetry and actionable operational intelligence. You don’t just see numbers; you possess a deep mechanical and electrical empathy that allows you to read a system’s data as a doctor reads a patient's chart. You are highly inquisitive, approaching complex anomalies without bias to uncover true root causes.

This is not a "hide behind the keyboard" role. You thrive in a hands-off environment, treating your space with a sense of proactive ownership and treating your peers as fellow experts. You are a truth-teller who uses thorough, compassionate communication to persuade others and drive impact in the high-stakes world of data center uptime. We expect our Data Scientists to arrive ready to own their space and contribute to the team’s collective success immediately.

**We are seeking a U.S.-based team member (Pacific Time Zone preferred) with flexibility to work hours that overlap with APAC time zones as needed. 

Responsibilities

You will utilize our existing data ingestion and delivery platforms to "teach" our models to understand the physical world, filling a critical expertise gap in the data center industry.

• Multidisciplinary Diagnostic Analysis: Use telemetry tools to analyze sensor data across mechanical (chillers, pumps) and electrical (UPS, switchgear, power feeds) systems to identify "failure signatures" for our LLM-driven monitoring tool.
• Refining the Logic Engine: Act as a primary user of our platforms, identifying gaps in our current mechanisms and collaborating with Engineering to influence future features and data quality.
• Operational Insight Generation: Translate raw telemetry into the "SME-level" logic and directions used by our LLM tool to guide data center operators in real-time.
• SME Development: Cultivate deep domain expertise in all facets of data center infrastructure. You will be expected to master the nuances of both mechanical and electrical dependencies to ensure our product reflects operational reality.
• Customer Guidance: Move from shadowing peers to directly supporting customers, using our platform to provide clear, data-backed direction on complex problems.
• Model Validation: Oversee pilot projects to test how our AI-driven SME tool interprets real-world stressors, ensuring the output is operationally realistic, accurate, and actionable.
• Adaptability: Remain agile and proactive. As a member of a fast-moving team, you will encounter challenges and scopes not explicitly defined here; we expect you to lean in and solve them.

Key Qualifications

• Experience: 2–3 years of professional relevant experience
• Educational Background: Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Control Theory, or a related field that provides a foundation in physical systems and thermodynamics.
• Analytical Grit: A deep, innate interest in using data to diagnose how and why systems fail. You are a "tinkerer" who prefers solving real-world problems over theoretical research.
• Technical Proficiency: Strong Python skills and experience with data manipulation libraries (Pandas/NumPy) to perform custom analysis outside of standard tooling.
• Communication Mastery: Ability to explain complex diagnostic findings clearly and persuasively to both technical peers and non-domain stakeholders.
• Unbiased Problem-Solving: A proven ability to look at a problem without preconceived notions and figure out solutions either independently or via team collaboration.
• Alignment with Values: Demonstrated commitment to Transparency, Collaboration, and Ownership—especially in environments where reliability and learning from failure are paramount.

Preferred Skills & Experience

• Infrastructure Exposure: Experience with critical infrastructure components (HVAC, power distribution, or industrial automation).
• Industrial IoT: Experience with time-series data from industrial sensors (SCADA, BMS, Smart Meters).
• AI/LLM Curiosity: Exposure to or a strong interest in how LLMs can be used for root-cause analysis and automated reporting.

Onboarding

In your first 30 days…

• Familiarize yourself with the company handbook and team roadmap.
• Review existing system ontologies and sensor data structures across both mechanical and electrical domains.
• Shadow senior team members during customer diagnostic reviews to understand the "voice" of the SME.

In your first 60 days…

• Build full proficiency in our internal data tools and analysis workflows.
• Identify failure signatures in customer data with peer guidance and begin automating detection logic.
• Identify at least one gap in our current tooling and propose a logic-based solution to Engineering.

In your first 90 days…

• Provide direct guidance to customers on anomalies with peer support, moving toward full self-sufficiency.
• Contribute to the refinement of the LLM "instruction set" for cross-disciplinary diagnostics.
• Present a post-incident analysis correlating telemetry to a real-world root cause to the broader product team.

General Interview Process

All of our interviews are held via Google Meet, and an active camera connection is required.

1. Meeting with People Operations team member (30 minutes)
2. Meeting with Hiring Manager (60 minutes)
3. Technical Interview with Data Science team member (60 minutes)
4. Meeting with Program Manager (60 minutes)
5. Culture fit interview with Phaidra’s co-founders (30 minutes)

Base Salary

US Residents: