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 

About the Role

We’re looking for a Director of Engineering to lead our Intelligent Messaging group—one of the most critical and high-impact areas at Attentive. This team powers the systems behind billions of personalized messages (SMS, email, push) sent every month, helping the world’s leading brands connect with consumers in smarter, more meaningful ways.

At the core of this is AI, machine learning, and real-time data. This allows us to drive personalization at massive scale - turning every message into an opportunity to engage, convert, and build long-term customer relationships.

In this role, you’ll lead multiple teams and play a key role in defining how AI shapes the future of messaging at Attentive. You’ll partner closely with Product and Engineering leadership to build and scale systems that are fast, reliable, and deeply intelligent. You’ll stay close to the work - guiding architecture, unblocking complex problems, and stepping in when it matters - while also building strong teams and developing great managers.

This is a role for someone who likes to operate deep in the systems, close to the people, and aligned with the business. You’ll own the technical direction of a high-scale, high-uptime platform and help us push what’s possible as we continue to grow.

This is a hybrid role based in NYC, with occasional travel to our SF office.

What You’ll Accomplish

• You’ll own the delivery of cutting-edge, AI-powered consumer messaging experiences used by millions
• You’ll manage and evolve a multi-team organization, build on our great culture, and set a high bar for engineering excellence
• You'll oversee the technical strategy in multiple domains, supporting various layers of our messaging applications by using existing and emerging technology platforms
• You’ll accelerate our engineering velocity using cutting-edge agentic and LLM tooling, while successfully managing safety and stability
• You’lll collaborate with product, ML, design, and data science to shape the roadmap - not just execute on it
• You’ll work directly with partner teams and stakeholders in the platform, go-to-market, and customer success organizations

Your Expertise

• Above all else, you are technical and love to dive deep to understand architecture, code, and infrastructure. This is the most critical attribute for success at Attentive.
• You have 10+ years of industry experience, including managing teams of 30+ engineers, and at least 2 years managing managers. From a technical perspective, you have 8+ years of experience in software engineering roles, ideally reaching staff level as an individual contributor.
• You embrace agentic workflows, and understand the benefits, complexity and risks of the fast-moving AI ecosystem
• You care about software quality and have a track record of building reliable, high-uptime systems, particularly in data-intensive environments
• You’re comfortable operating in fast-moving, high growth environments, translating business needs into the right levels of implementation

What We Use

• Our backend is Java / Kotlin / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, Aurora, AirFlow, Postgres, and Redis, hosted via AWS
• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS, using tooling like Istio, Datadog, Terraform, CloudFlare, and Helm
• 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, industry-leading LLMs, lots of data and tech like 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 $250,000 - $350,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

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This role requires a hybrid schedule and will be based in our New York, NY office (Tuesday through Thursday) and work fully remotely on Mondays and Fridays each week.

For The Points Guy website click here. Curious how The Points Guy fits into Red Ventures? Click here.

We're looking for a sharp, analytically rigorous Senior BI Analyst to join our growing Business Intelligence team. This is a hands-on, high-impact role at the center of how we understand and grow our business. You'll play a key role in the foundation of our data visualization ecosystem, build performance dashboards that drive decisions, conduct complex analyses to inform revenue-driving workstreams, and translate data into stories that non-technical stakeholders can act on. The right candidate is deeply comfortable with complicated datasets and cross-functional communication.

What You’ll Do:

• Architect and write the semantic layer for our new data visualization platform as we migrate from our current tooling.
• Build, iterate, and maintain dashboards and reports that give business stakeholders clear visibility into performance across the funnel.
• Own weekly full-funnel performance reporting, surfacing trends, anomalies, and opportunities with clear business context.
• Conduct ad hoc, multi-step analyses using advanced statistical methods, complex SQL queries, and Python scripts to answer granular business questions.
• Understand and improve existing data pipelines in partnership with Data Engineers, understanding data flows end-to-end.
• Present findings to business stakeholders, translating highly technical analysis into clear, actionable insights.
• Proactively identify areas for measurement improvement, optimization opportunities, and testing.
• Leverage AI tools to accelerate work, using your own judgment and expertise to critically evaluate and improve AI outputs

What We’re Looking For:

• 3+ years of experience in a highly quantitative and analytical environment.
• Comfort in a fast-paced and often changing environment, with an inclination to solve new problems and learn new skills
• Bachelor's or Master’s degree in Data Science, Statistics, Mathematics, or a related quantitative field preferred. 
• Strong SQL and Excel
• Python (Pandas, Nmpy, Statsmodels)
• Experience in or exposure to BI/data visualization tools (Tableau, Looker, or similar)
• Familiarity with data warehouse environments (Snowflake, BigQuery, Redshift)
• Understanding of data pipelines and semantic layer concepts

Compensation: 

This range reflects total cash compensation, which may include base salary only or base salary plus target bonus, depending on the role. Where eligible, equity may also be offered separately and not included below. Actual compensation varies based on location, experience, and qualifications.

• Total Cash Compensation Range: $100,000 - $140,000 per year

*New York City Total Cash Compensation Range: $125,000- $170,000 per year

Additionally, the following benefits are provided by Red Ventures, subject to eligibility requirements.

• Health Insurance Coverage (medical, dental, and vision)
• Life Insurance
• Short and Long-Term Disability Insurance
• Flexible Spending Accounts
• Holiday Pay
• 401(k) with match
• Employee Assistance Program
• Paid Parental Bonding Benefit Program
• Flexible Paid Time Off (PTO): We believe time to rest and recharge is essential.  That’s why we offer a generous and flexible PTO policy.  Full-time employees accrue 20 days of PTO for a full calendar year annually, with an increase to 25 days after five years of service.

Who We Are:

Red Ventures is a global portfolio of high-growth companies — spanning several U.S. businesses, a joint venture in the health services industry, and strategic investments in Europe. Their businesses include The Points Guy, Lonely Planet, Bankrate, the Allconnect Platform, RV Home Client Growth, RV Growth & Transformation, Sage Home Loans Corporation, and more. Across the portfolio, Red Ventures businesses deliver seamless digital experiences for consumers, help Fortune 100 clients solve large-scale digital growth challenges, and create world-class experiences and opportunities for employees. Learn more at redventures.com and follow @RedVentures on LinkedIn and Instagram.

At Red Ventures, we believe diverse, inclusive teams are better. To help you better understand our core values and beliefs, we encourage you to watch this brief YouTube video: Our Belief Statements. This will give you insight into the principles that guide our work and our commitment to fostering an inclusive environment.

Red Ventures is an equal opportunity employer that does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or any other basis protected by law. Employment at Red Ventures is based solely on a person's merit and qualifications. 

We are committed to providing equal employment opportunities to qualified individuals with disabilities. This includes providing reasonable accommodation where appropriate. Should you require a reasonable accommodation to apply or participate in the job application or interview process, please contact accommodation@redventures.com. 

If you are based in California, we encourage you to read this important information for California residents linked here.

At Red Ventures, we believe in real human connection. That’s why we do not hire someone through text, social media, or email only. As part of the hiring process, you should expect live conversations with RV teammates before any offer is made. Also, keep an eye on the sender: we only use official @redventures.com email addresses at the portfolio level or business specific email addresses (e.g., @thepointsguy.com), not ones like “redventurescareer.com.” We will never ask candidates to send money, buy equipment, or share financial account info during your journey with us. You can always find our open roles on redventures.com— if you receive a message that seems suspicious, please use redventures.com to verify the opportunity.

For more, the U.S. Federal Trade Commission has published helpful articles to help individuals learn more about protecting themselves from recruiter scams. If you think you’ve been targeted, feel free to report it to your local authorities. Stay safe out there!

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#BR

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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By applying for this position, your data will be processed as per Attentive's Privacy Policy.

Location: Remote, New York City, or Oakland

• Travel of approximately one week per quarter may be required. 

Role Type: Full-time

Compensation:  $97,000

Visa sponsorship: Not available

Hires remotely in: United States

Experience: 2+ years

Recidiviz is thrilled to be hiring a Policy Data Analyst to join our team! We’re a small, fast-moving group that works with complex criminal justice data from our state partners and develops analyses and tools that target the drivers of incarceration. That’s where you come in. We’re looking for someone who has creativity and inquisitiveness to identify and solve open-ended problems, clarity to think through complex and variable data, flexibility to adjust in a rapidly evolving environment, and above all else, a collaborative, kind nature to add to our culture.

About us

Recidiviz is creating safer, healthier communities by improving outcomes for people in the criminal justice system. We build technology to reduce the number of people in prison and to help criminal justice leaders embrace data-driven decision-making. 

Using software tools and thoughtful product design, we’ve been able to safely and permanently reduce incarceration and improve outcomes. We work side-by-side with leaders of the criminal justice system, people in prison and on supervision, and ecosystem partners to build a better path forward. In addition to the revenue we earn from state partners, some of the most respected philanthropists and foundations support our work.

People who succeed at Recidiviz lead with kindness and humility, assume good intent, learn from failure, and fix problems when they see them. They are excited to work arm in arm with government leadership and staff to improve outcomes. They are great listeners. They build deep relationships with and empathy for the people we work with and the people who our mission serves, even when those two groups feel at odds. 

About the role

Recidiviz’s policy team supports state DOC leaders that want to rewrite old policies or implement new ones, rooted in evidence and analytics, to improve outcomes, increase public safety and community health, and drive meaningful changes. We tailor data analysis, built on detailed DOC data, to answer questions like: What combination of criteria best select for probation clients who are safe to discharge? What static factors influence parole decisions today and how would that change if new, dynamic factors were added? How many people would X, Y, or Z adjustment to a policy affect and what can we say about the affected group? By translating concepts into concrete modeling, we help drive smarter and more ambitious change.

This role collaborates across several teams to guide work that targets the drivers of incarceration. Our Policy Data Analysts work with diverse data – criminal justice data both raw and processed from across the country, reports and policy documents from government agencies, and much more – to develop the policy analyses that deepen our understanding of the criminal justice system and motivate policy change. Our Policy Data Analysts translate policy concepts into quantitative metrics, perform analyses, and play a key role in contextualizing and presenting their analyses to stakeholders, both internal and external. 

Travel of approximately one week per quarter may be required. 

Core responsibilities

• Leveraging criminal justice datasets to generate context-responsive insights that expand  momentum for policy reform
• Adapting analytical methods to evidence detailed policy concepts and quantify policy-design tradeoffs
• Contextualizing and communicating key findings to internal and external stakeholders
• Collaborating with our Data Science and Implementation Engineering teams to design and execute on targeted roadmaps that drive impact in the states where we work
• Collaborating with our Product Management and State Engagement teams to bring analyses and data modeling into administrative and legislative policy processes

Wild success

A year from now:

• You’ve driven impact. Your work has informed several policy reforms across the country and has helped quantify the impact those reforms are having on the outcomes of the justice system.
• You’ve leveled up our analytical team. Your contributions to our analytics and processes, as well as your support for your teammates, has helped set our team up to achieve more impact sooner.

Minimum qualifications

• Strong communication and collaboration skills, to help nurture a knowledgeable, data-oriented culture 
• Enthusiasm for working with internal and external partners from diverse backgrounds and worldviews, such as government staff, legislators, political consultants, researchers, journalists, technical staff, and practitioners in criminal justice reform
• Sufficient math or statistical background to reason about analysis design, examine results closely, and prepare data and analyses that are usable for various applications
• 2 or more years of practical experience exploring, analyzing, and processing complex datasets
• Professional work experience using SQL to work with large datasets, including high proficiency writing efficient queries for more complex data extraction and transformation tasks
• High familiarity with Python, specifically Pandas package, for tasks such as statistical analysis and data visualization

Preferred qualifications

• Ability to discern when and how analysis is actionable for stakeholders; ability to “wear your public servant hat” while conducting analysis
• Experience adapting quantitative methods that introduce intuitively meaningful metrics in ambiguous, unconstrained contexts
• Experience balancing depth and speed when navigating short timelines and shifting priorities
• Experience working with large datasets from the public sector, especially related to criminal justice
• Familiarity with our data stack, which includes Google Cloud Platform, BigQuery, Looker, Jupyter notebooks, and Python/Pandas

Compensation

Compensation is standardized based on roles and responsibilities. This ensures equitable compensation and responsible stewardship of our resources. As such, we do not negotiate compensation offers. 

The compensation for this role is: $97,000.

What we offer

• Effective, extremely thoughtful colleagues, working together on a mission that matters
• 90% medical, dental, and vision insurance coverage for you and your dependents
• Flexible time off, including 20 days of PTO, 3 days of paid volunteering time, and 13 paid holidays
• 12 weeks of paid parental leave
• 401(k) retirement plan with 5% company match and no vesting period
• Complimentary One Medical membership (depending on location)
• Partnership with Carrot to provide employees with inclusive fertility and family-forming benefits, as well as a small but growing number of hormonal health and gender-affirming care benefits
• Monthly ClassPass credit for personal wellness
• Free mental health support via Talkspace
• Well-located offices in Oakland and Manhattan, with the flexibility to work remotely or go into either office as you choose
• An annual company offsite each spring and other ad-hoc gatherings
• All the exhilarating challenges and stretch opportunities of a tech startup, combined with the mission-driven heart of a nonprofit

More about Recidiviz

Recidiviz was an all-volunteer effort until early 2019, when Clementine, Andrew, and Joshua founded the organization. Since then, we’ve built an A-team of software engineers, designers, product managers and domain experts, from companies like Google, Apple, Dropbox, Opower, and Sidewalk Labs. Recidiviz was part of Y-Combinator’s 2019 class and has received support from some of the most respected philanthropists and foundations, including Ford Foundation, Mackenzie Scott, Schmidt Futures, Arnold Ventures, Chan Zuckerberg Initiative, and the Mozilla Foundation.

Today, Recidiviz works with (and earns revenue from) over 18 state partners – big and small, red and blue – and covers more than 40% of the US incarcerated population. We have helped to get tens of thousands of people out of the criminal justice system, safely and equitably, and saved states nearly $1 billion. In the next five years, Recidiviz plans to partner with 40 states and help 250,000 people who are stuck in the system to get out and stay out. In addition to partnering with state Departments of Corrections, Recidiviz collaborates with and learns from partners – from organizations like the Correctional Leaders Association (CLA) to community based organizations and justice-impacted individuals, whose perspectives guide our work.

To learn more about how we do what we do, check out our 2024 Year in Review, read some press coverage, or watch our TED Talk. And if you’re really keen to see our work, you can dive into our Github :).

An important note

Lasting change is always built on diversity. Recidiviz recruits, employs, trains, compensates and promotes regardless of race, religion, color, national origin, sex, sexual orientation, disability, age, veteran status, ancestry, citizenship, marital status, gender identity and all protected status as required by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a special need that requires accommodation, please let us know in your application. Even if you don't think you meet all the criteria above, drop your resume, and we'll take a look – you might be great for another role or another time!

About the role:

We are seeking an exceptional Applied Scientist to work on core search systems that power our product, with a particular focus on provider selection and recommendation algorithms. You will play a pivotal role in shaping how Garner selects high-value providers for members by developing the evaluation frameworks, objective functions, and algorithms that drive our search experience.

This role is ideal for someone who is excited by ambiguous, high-impact problems and can translate messy real-world constraints into robust algorithmic systems. You will partner closely with Product and Engineering to design and deliver production algorithms that balance provider quality, affordability, and access.

Where you will work:

This role will be based in our New York City office. You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. 

What you will do:

• Build and own the algorithms that power Garner’s search
• Design objective functions, scoring frameworks, and decision logic that balance competing goals such as quality, cost, and access
• Translate ambiguous product and business problems into rigorous algorithmic approaches that can be deployed in production
• Partner with engineers to productionize systems at scale
• Identify where applied machine learning, optimization, heuristics, or rules-based methods are the right tool for a problem
• Develop a strong understanding of the healthcare economy

The ideal candidate has:

• 4+ years of experience using Python and SQL to build production, data-driven algorithms
• Strong applied problem-solving skills, with the ability to define good metrics and design algorithms under ambiguity
• Strong judgment in choosing between statistical models, heuristics, optimization approaches, and simpler algorithmic methods depending on the problem
• Strong communication skills and the ability to synthesize complex algorithmic ideas for business and technical stakeholders
• A desire to be a part of a high-performing, mission-driven team that operates with urgency, a strong sense of individual accountability, and a commitment to authentic feedback

Technologies we use: 

• Python, SQL, AWS, Snowflake, pandas, XGBoost

This is a unique opportunity to join a fast-growing company in a transformative role, helping shape the future of healthcare.

Please note: we are unable to sponsor or take over sponsorship of an employment visa at this time.

Compensation Transparency:

The target salary range for this position is $200,000 - $240,000. Individual compensation for this role will depend on various factors, including qualifications, skills, and applicable laws. In addition to base compensation, this role is eligible to participate in our equity incentive and competitive benefits plans, including but not limited to: flexible PTO, Medical/Dental/Vision plan options, 401(k) with company match, flexible spending accounts, Teladoc Health and more.

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 Description

• As an Senior Value Engineer specializing in CPG and Fleet Logistics, you are pushing the envelope in solving business-critical problems for some of the world's most recognized consumer brands and global mobility networks. You will be working intimately with our most strategic enterprise clients, understanding their uniquely complex objectives—spanning from high-velocity beverage manufacturing and Direct Store Delivery (DSD) optimization to massive-scale fleet lifecycle management and dynamic asset routing. You will build Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customers' massive supply chains, vehicle fleets, and distribution networks. This enables them to industrialize AI, unlocking real ROI on deployments at scale—ensuring products are always on the shelf and vehicles are always ready for the customer. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Chief Supply Chain Officers (CSCOs) and Fleet Operations Executives, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis across these premier global networks.

Key Responsibilities:

• AI Discovery & Solutioning: Understand the clients' overarching AI strategies and the distinct supply chain challenges inherent to high-volume CPG and fleet mobility (e.g., predictive demand forecasting, route optimization, fleet predictive maintenance, dynamic asset allocation, and mitigating raw material volatility). As a Celonis product and logistics domain expert, translate these complex, physical-world challenges into innovative AI solutions that drive measurable impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle within various manufacturing, distribution, and fleet management business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and telematics networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, and DSD execution.

• Agentic Process Transformation: Support these enterprise clients in achieving tangible ROI from AI at scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous fleet rebalancing, intelligent shipment exception handling, or automated trade promotion deductions).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs (e.g., SAP), Transportation Management Systems (TMS), Warehouse Management Systems (WMS), and massive IoT/telematics data streams.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for CPG and Mobility Supply Chains, scaling knowledge across the organization regarding the nuances of fast-moving consumer goods and asset-heavy fleet operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, CPG/Beverage, or Fleet Logistics environments. This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume manufacturing and mobility (such as Direct Store Delivery (DSD), Order-to-Cash, Procure-to-Pay, Fleet Lifecycle Management, or Sales & Operations Planning) with the ability to translate high-level operational needs into specific AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent dispatch assistants, or automated extraction of data from complex vendor contracts and logistics documentation).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional and IoT datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, logistics directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for enterprise-grade supply chain environments.

• Familiarity with CPG and fleet-specific systems (e.g., SAP APO/IBP, Blue Yonder, Manhattan, or major telematics/fleet tracking platforms).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

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 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: 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 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

DRW is a major Chicago-based proprietary trading firm founded in 1992 by Don Wilson, specializing in diversified, technology-driven market-making and quantitative trading across asset classes including fixed income, options, derivatives, commodities, energy, equities, FX, and cryptocurrency.

DRW is building out a dedicated prediction markets desk focused on platforms such as Polymarket and Kalshi. As a Prediction Markets Trader, you will develop, execute, and optimize high-conviction trading strategies in binary event contracts. You will manage a live portfolio, targeting consistent positive expectancy through market making, microstructure exploitation, cross-platform arbitrage, event-driven momentum, and statistical models. This role requires genuine, demonstrated passion for prediction markets, strong quantitative reasoning, and the ability to operate in thin, volatile, event-resolution-driven environments.

Core Responsibilities:

• Monitor and trade active markets in real time across Polymarket (CLOB/Gamma/Subgraph APIs) and Kalshi (FIX/WebSocket/REST).
• Execute strategies including: market making with dynamic skew, microstructure arbitrage (order-flow and book-imbalance sniping), cross-platform arb, news/event momentum (sub-second reaction), and statistical pairs/mean-reversion.
• Develop and backtest models using historical tick data, Bayesian probability updates, NLP sentiment parsing, and ML for fair-value estimation.
• Collaborate with engineering on low-latency infrastructure (API integrations, order engines, anomaly detection).

Required Qualifications:

• Bachelor's or higher in Quantitative Finance, Statistics, Computer Science, Economics, Mathematics, or equivalent.
• Strong programming skills: Python (pandas, NumPy, backtesting).
• Solid foundation in probability, statistics, time-series analysis, and Bayesian methods.
• Hands-on experience with prediction market platforms (Polymarket and/or Kalshi APIs) or closely related domains (options, binary events, sports/event betting).
• Genuine, demonstrated interest in prediction markets — we expect you to be actively engaged with the space (personal trading, deep reading of protocols, following major resolutions, contributing to discussions, etc.). This is non-negotiable.

Highly Valued (but not strictly required):

• Prior profitable trading experience in prediction markets, options, or event-driven strategies (personal or professional).
• Familiarity with blockchain/DeFi tools (ethers.js, Polygon RPC, USDC wallets).
• Experience with low-latency systems, FIX protocol, or Web3 integrations.
• Track record of building and backtesting quantitative models with real historical data.
• Deep domain knowledge of high-impact events (politics, macroeconomics, climate, sports).

Who We’re Looking For: We are especially interested in exceptionally sharp, self-motivated individuals — including strong campus hires and new graduates — who are obsessed with prediction markets and can demonstrate clear, substantive engagement with the space. If you’ve been actively trading Polymarket/Kalshi, analyzing resolutions, building personal models, or following the ecosystem closely, we want to talk to you.

Apply With: 

• Resume
• Cover letter explicitly detailing your genuine interest in prediction markets (specific examples of your engagement: trades you’ve made, resolutions you’ve studied, models you’ve built, protocols you follow, etc.)
• GitHub, personal blog, or portfolio links showing relevant work

Applications reviewed on a rolling basis. Strong candidates will receive a technical screen, strategy discussion, and live coding/modeling exercise focused on real prediction market scenarios.

Location:  Flexible.  US-based preferred.

The annual base salary range for this position is $175,000 to $200,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus.  In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

#LI-GV1

Mid-level Applied AI Data Scientist (Tableau Focus)

Location: New York, NY (Hybrid – 3 days in-office) | Practice Area: Technology & Engineering | Type: Permanent

Turn data into insight, and insight into impact.

The Role
We are looking for a Data Scientist to join us, working at the intersection of data, machine learning, and business insight. In this role, you will apply statistical and machine learning techniques to real-world problems, helping clients unlock value from complex datasets. You will collaborate with cross-functional teams and contribute to the development of scalable, data-driven solutions.

What You’ll Do

• Apply statistical analysis, clustering, and probabilistic techniques to generate actionable business insights
• Work with structured and semi-structured datasets to identify patterns, trends, and anomalies
• Build and support NLP workflows, including named entity recognition (NER), entity resolution, and text classification
• Develop machine learning models with guidance from senior team members, contributing to evaluation and refinement
• Create Tableau dashboards and visualizations to communicate insights to technical and non-technical stakeholders

What We’re Looking For

• 3–7 years of experience in data science, analytics, or applied machine learning
• Strong foundation in statistics, probability, and core machine learning techniques (e.g., regression, classification, clustering)
• Hands-on experience with Python and libraries such as pandas, NumPy, and scikit-learn
• Experience building Tableau dashboards to clearly communicate data insights
• Ability to collaborate across teams and translate analytical findings into business-relevant outcomes

Bonus Points For

• Experience working with graph-like or network datasets
• Exposure to ML Ops practices such as experiment tracking, model versioning, and monitoring
• Hands-on experience with NLP techniques such as entity extraction or text processing
• Familiarity with cloud-based data or ML platforms
• Experience contributing to rapid prototyping or iterative AI solution development

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions
• Work in a collaborative, flat, and entrepreneurial consulting culture
• Access continuous learning, training, and industry certifications
• Be part of a team shaping the future of digital financial services
• Help shape the future of digital transformation across FS & Energy.

Use of Artificial Intelligence in Talent Acquisition
At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination.

AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

Benefits

• Medical, Dental, Vision coverage
• 401(k) with employer match
• Maternity and paternity leave, plus dependent care support
• Tuition reimbursement and wellness reimbursement programs
• HSA, FSA, commuter benefits, and employee discount marketplace access

Inclusion at Capco
We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

We have been informed of several recruitment scams targeting the public. We strongly advise you to verify identities before engaging in recruitment related communication. All official Capco communication will be conducted via a Capco recruiter.

#LI-MB1

#LI-HYBRID

Project Overview

This is a cutting-edge initiative to integrate Large Language Models (LLMs) with WorldQuant's proprietary strategy management tools. The project aims to provide AI-assisted insights, automate routine analytical tasks, and enable natural language interactions for Portfolio Managers to more efficiently analyze, maintain, and enhance their trading strategies. This involves building foundational infrastructure, developing robust data pipelines for metrics and features, and creating a secure, user-centric interface with a strong focus on protecting intellectual property.

The Role:

We are seeking a talented and motivated Full-Time Software Engineer to play a key role in the development and enhancement of this AI-driven platform. You will be responsible for designing, building, and maintaining critical components of the system, primarily focusing on the Model Context Protocol (MCP) servers that form the backbone of the platform. This includes enhancing existing MCPs, such as our proprietary command-line interface for strategy data, developing new MCPs for internal data system integration, strategy analysis, and performance metrics, and contributing to the secure and effective use of LLMs.

Key Responsibilities

• Design, develop, test, and deploy robust and scalable MCP servers and related tools in Python.
• Enhance existing MCPs, including our internal data access tools, to ensure reliable access to strategy metadata, historical PnL data, and PnL attribution by risk factors.
• Develop new MCPs, including but not limited to MCPs for direct data system integration, MCPs for strategy analytics, and MCPs for performance reporting.
• Design and implement secure prompt engineering techniques to interact with LLMs, ensuring effective information retrieval while minimizing the risk of intellectual property leakage.
• Collaborate with project managers, technical leads, and other developers to define technical specifications and integrate various data sources.
• Work on API development and integration, ensuring seamless data flow between different systems (internal knowledge management systems, simulation systems, data warehouses).
• Implement data parsing and manipulation logic for various formats (JSON, CSV).
• Contribute to the design and implementation of data pipelines for strategy metrics and features.
• Address and resolve bugs and issues in existing MCP tools and infrastructure.
• Participate in code reviews, and contribute to unit and integration testing efforts.
• Create and maintain technical documentation for developed components.
• Stay updated with emerging technologies and methodologies in AI, LLMs, prompt engineering, and financial technology.

What You’ll Bring:

Core Skills:

• Strong proficiency in Python programming.
• Proven experience in API development, integration, and consumption.
• Solid understanding of database interaction, data access patterns, and data modeling.
• Experience with data parsing and manipulation libraries and techniques (e.g., pandas, JSON, CSV).
• Understanding of or experience with prompt engineering principles for Large Language Models
• Awareness of data security and intellectual property protection considerations in the context of AI and LLM applications

Domain-Specific Knowledge (Highly Beneficial):

• Familiarity with financial data (e.g., PnL, Sharpe ratio, alpha, risk factors, AUM).
• Experience with quantitative trading systems, market data systems, or strategy management platforms (familiarity with internal data systems or command-line data tools is a significant plus).

Technical Environment Familiarity (Helpful):

• Experience working in a Linux environment.
• Understanding of Command Line Interface (CLI) tools and development.
• Familiarity with version control systems (e.g., Git).

Soft Skills

• Excellent problem-solving and analytical skills.
• Strong collaboration and communication skills, with the ability to work effectively in a team.
• High attention to detail and commitment to delivering high-quality software.
• Ability to learn quickly and adapt to new technologies and complex systems.

Education

• Bachelor's or Master's degree in Computer Science, Engineering

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

What you’ll do

About the internship

Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2026. This is an exceptional opportunity to contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.

As an intern, you'll tackle challenging problems at the intersection of finance, technology, and data. You'll have the chance to work on creative projects like the Stripe Assistant and the Stripe Foundation Model, which leverage machine learning to revolutionize how businesses interact with financial services and data.

Responsibilities

• Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
• Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
• Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
• Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
• Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.

Who you are

Minimum requirements

• A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
• Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
• Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
• Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
• A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.
• Intent to return to the degree-program after the completion of the internship/co-op.

Preferred qualifications

You Might Also Have:

• Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
• Published and presented peer-reviewed articles in top-tier venues.
• Experience in writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
• Familiarity with navigating new codebases and managing work across different programming languages.
• Excellent written communication skills to clearly articulate your work to both team members and wider Stripe audiences.

Application requirements

Please submit the following with your application:

• A detailed resume or LinkedIn profile showcasing your work history.
• Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.

Join us for an unforgettable summer internship and help shape the future of global commerce. At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.

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

Your Core Responsibilities

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

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

Your Skills and Experience

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

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

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

#LI-DNI

Position Summary

We are seeking a skilled Machine Learning Engineer with approximately three years of hands-on experience designing, deploying, and maintaining production-grade machine learning systems. In this role, you will collaborate closely with data scientists, software engineers, and product teams to translate research models into reliable, scalable, and high-impact applications. You will be deeply involved in the end-to-end ML lifecycle—from data ingestion and feature engineering to deployment, monitoring, and continuous improvement—playing a critical part in shaping our machine learning platform and capabilities.

Primary Responsibilities

• Develop, deploy, and optimize machine learning models for real-world business use cases and client-facing applications.
• Partner with data scientists to operationalize predictive models and ensure scalable, maintainable, and performant production deployments.
• Design and implement data pipelines and workflows that support training, inference, and model lifecycle management.
• Work with large, complex datasets to ensure data quality, reproducibility, and reliable version control across ML workflows.
• Implement model monitoring, logging, and alerting strategies to track performance, detect drift, and support retraining cycles.
• Leverage cloud platforms (AWS, Azure, GCP) to build scalable ML solutions using managed services and infrastructure-as-code practices.
• Write clean, modular, and well-documented code aligned with MLOps and software engineering best practices.
• Stay current on emerging ML tooling, frameworks, and industry best practices to continuously enhance our platform and capabilities.

Qualifications

• Master’s degree in Computer Science, Data Science, Engineering, or a related technical field.
• 6+ years of experience in machine learning engineering, applied ML, or related software engineering roles.
• Strong proficiency in Python and experience with modern ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with distributed data processing and compute frameworks (e.g., Pandas, Spark, Dask).
• Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
• Familiarity with CI/CD pipelines, testing automation, and version control using Git.
• Experience working with cloud-based ML platforms or services (e.g., SageMaker, Vertex AI, Databricks, or Snowflake ML) is preferred.
• Strong understanding of model evaluation, feature engineering, and performance optimization in production contexts.
• Excellent analytical, communication, and collaboration skills, with the ability to work effectively in cross-functional teams.

This is an exempt position. The annualized base pay range for this role is expected to be between $140,000-$180,000.  Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed, and the applicant's skill set.  The base pay is just one component of the total compensation package for employees.  Other rewards may include an annual cash bonus and a comprehensive benefits package, including but not limited to medical, dental, vision, life and 401(k). Please note that the job title is subject to change based on the selected candidate’s experience and education.

About the Role 

In this role, you will build and lead our forward-deployed engineering (FDE) team, working directly with leading labs and enterprises to scope, build and deliver high quality datasets to support their most critical AI initiatives. 

You’ll lead a team that will own quality in the end-to-end data pipeline. This will include working with customers to define what “good” data looks like to implement the relevant workflows in their platform. You will design innovative ML approaches to enhance human-in-the-loop (HITL) techniques and improve the efficiency of data generation and review processes. Your team will own systems and tools that enable consistent, scalable, and high-quality data delivery to our customers.

Sitting at the critical intersection of data engineering, ML engineering, operations, and customer engagement— leading scoping and preselling efforts.  You'll also partner closely with the Snorkel delivery team and cross-functional stakeholders to define quality standards, develop measurement frameworks, drive ML-based workflows to improve data pipelines and unblock projects through technical innovation. As the founding member, you’ll also roll up your sleeves to define and own the workflows and processes that are needed to deliver exceptional data at scale.

Main Responsibilities

• Build and lead the Forward Deployed Engineering DaaS organization, setting a clear vision, defining the operating model and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
• Build, mentor, and motivate high performing teams, including cultivating skills and culture needed to consistently deliver exceptional outcomes and transformative impact. 
• Own and evolve the data pipeline components of the DaaS stack, including model-assisted labeling and data generation, quality estimation, and data-centric feedback loops that guide human input
• Partner with customers - including research and engineering teams at Frontier AI Labs - to scope requirements for complex, novel AI datasets and translate needs into delivery-ready workflows 
• Develop robust systems for request intake, task orchestration, SLA tracking, and progress monitoring to ensure seamless execution and prevent critical delivery gaps
• Collaborate cross-functionally with research and engineering teams to innovate, develop, and productionize HITL data generation methods, advanced quality techniques, and improve internal delivery tooling
• Drive continuous improvement by developing reusable workflows, surfacing operational insights, and enabling the organization to scale faster while maintaining high quality

What We’re Looking For

• 10+ years of experience in applied data or ML engineering roles, including 5+ years leading high-performing technical teams in hands-on management capacity
• Demonstrated success in customer facing roles, with a strong enthusiasm for data pipelines and LLM-based workflows.
• Proven track record of managing technical field teams in fast-paced, delivery-focused environments with competing priorities
• Experience as a player-coach—comfortable being hands-on while supporting and scaling the team
• Proven ability to thrive in fast-paced, ambiguous environments with cross-functional stakeholders
• Strong practical experience with LLM-based workflows, Python, SQL, and data tooling (e.g., pandas, Plotly, Streamlit, Dash)
• Bonus: experience working with data annotation workflows or internal tooling for data delivery orgs

Why Join Snorkel AI?

At Snorkel AI, we're building the future of data-centric AI. Our Expert Data-as-a-Service organization partners with world-class customers to solve some of the hardest data challenges — creating training and evaluation data that power the next generation of LLMs and AI systems. You'll work directly on projects that impact real production systems, while shaping how internal teams deliver faster, better, and more intelligently. This is a rare opportunity to found a function and have a broad, lasting impact across the company.

The Team

Discretionary & Client Solutions Technology is ~35 engineers across London, New York, and Sofia, building the platforms that power Man Group's discretionary investment and client facing operations. We operate at high tempo — shipping multiple production releases weekly across portfolio analytics, fund data platforms, client reporting, data pipelines, dashboards, and AI tools.

We are one of the most active AI-adopting engineering teams in Man Group — building LLM-powered agents, research tools with vector search, and AI integrations that our portfolio managers and analysts use daily. You'll have the opportunity to shape how AI is integrated into investment workflows.

The Role

This is a senior engineering role sitting at the intersection of Man Group's Discretionary (public markets) and Solutions technology teams in New York. You will be the primary NY-based engineer supporting portfolio managers, analysts and quants functions across both business lines.

The role spans Python data pipelines and analytics platforms serving Discretionary investment teams — equities, credit, and alternatives — alongside Python systems powering Solutions' fund analytics, portfolio management, and reporting infrastructure. You'll work hands-on building and operating production systems while acting as the key technical liaison for NY-based stakeholders.

Our Technology Stack

• Python (primary), TypeScript/React
• Data: Pandas, NumPy, Kafka
• Backend: FastAPI, Flask
• Frontend: React, Streamlit dashboards, Tableau
• Infrastructure: Kubernetes, Airflow
• AI tooling: Claude Code, LLM agents, vector search, RAG — we actively build and ship AI tools for our investment teams

Key Responsibilities 

Development & Delivery (70%)

• Build, extend, and maintain Python data pipelines using Pandas, NumPy, and internal libraries
• Develop and enhance portfolio analytics, risk reporting, and fund data platforms
• Contribute to AI-powered tools for investment teams — research databases with vector search, AI integrations for portfolio managers and analysts
• Build and maintain FastAPI and Flask backends and React/TypeScript frontends using our shared component libraries
• Deploy services to Kubernetes; manage Airflow DAGs for scheduled data workloads
• Collaborate with London and Sofia-based engineers on cross-team initiatives

Stakeholder Engagement (20%)

• Serve as the primary technical contact for NY-based Discretionary and Solutions stakeholders
• Gather requirements, translate business needs into technical solutions, and manage expectations
• Work directly with portfolio managers, analysts, and quants — understanding their workflows is as important as writing the code

Production Operations (10%)

• Own production stability for systems in your portfolio — investigate data quality issues, triage support requests, manage incident response
• Maintain documentation and operational processes

Key Competencies 

Essential

• 5+ years of professional software engineering experience with a strong delivery track record
• Strong Python: Well-tested, modular production code. Comfortable with dataclasses, type hints, OOP, design patterns
• Financial services experience — particularly portfolio management, risk, or investment operations
• Pandas/NumPy proficiency: Building efficient data pipelines and transformations at scale
• AI/LLM tooling — experience building with or integrating LLM-based tools. We're active early adopters of AI-assisted development and are building AI agents for our investment teams
• Solid testing discipline: pytest, unit tests, integration tests — you write tests as a matter of course
• Comfortable in a Linux environment with Git, virtual environments, and CLI tooling
• Strong communicator: You can explain technical decisions to non-technical stakeholders concisely, and you view stakeholder interaction as integral to good engineering — not overhead
• Self-directed: You manage your own priorities, flag blockers early, and drive work to completion with appropriate autonomy
• Degree in a STEM subject or equivalent practical experience

Advantageous  

• React/TypeScript for frontend development
• Experience with web APIs: Building and consuming RESTful services (FastAPI, Flask, or equivalent)
• C#/.NET familiarity — some Solutions systems are built in .NET. You won't be the primary .NET engineer, but being able to read and navigate the codebase is valuable
• Kubernetes & containerisation — deploying and troubleshooting services in k8s
• Airflow — building and maintaining scheduled data pipelines
• Distributed systems concepts — messaging architectures, event-driven design, caching strategies
• Experience working with geographically distributed teams — London will be your primary collaboration hub

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking a VP-level AI/ML Engineer to deploy AI solutions at enterprise scale, with a strong emphasis on Large Language Model (LLM) applications and modern MLOps & AIOps practices. This role sits at the intersection of data science and software engineering, reporting to the manager of the IT Application Development and Support team and working closely with the Chief Artificial Intelligence Officer, transforming innovative AI prototypes into robust, scalable production systems. The AI/ML Engineer will lead the deployment of high-impact AI capabilities (e.g., generative AI systems, personalization engines, automation tools) and ensure scalable AI platforms that deliver real-world value. The role also includes designing, constructing, and maintaining the Bank’s AIOps solution, with Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Production Architecture & AIOps

• Establish and enforce architecture standards for production AI systems, including data pipelines, model serving infrastructure, and real-time inference services.
• Implement AIOps/MLOps pipelines for CI/CD of ML models, model governance, monitoring, and lifecycle management.
• Design and maintain scalable software applications with integrated AI/ML capabilities.
• Develop software architecture and design patterns to ensure performance and scalability.
• Write clean, maintainable code in general-purpose programming languages (Python, Java, C, C++, Go).
• Implement and manage data pipelines for preprocessing and transforming data for AI/ML models.
• Integrate AI/ML models into production environments and optimize for reliability and scalability.
• Apply Site Reliability Engineering (SRE) principles and implement monitoring and alerting solutions.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay current with advancements in software engineering and AI/ML technologies.
• Adhere to agile and lean software development best practices.
• Thoroughly document all developed models and processes according to relevant policies and standards.
• Support the production environment by either resolving technical or functional issues, in line with the procedures defined by the Bank.

Cross-Functional Collaboration

• Partner with data scientists, AI scientists, product managers, data engineers, DevOps, and business stakeholders to operationalize AI algorithms.
• Mentor or train teams and coordinate between research-oriented AI scientists and engineering teams to continuously improve models with production feedback.

Scaling & Performance

• Ensure AI solutions perform at scale, handling thousands of daily inferences with low latency and high reliability.
• Optimize model serving using techniques like model compression, caching, and hardware acceleration.

Implement robust monitoring and alerting for model performance to detect and address degradation (e.g., drift, latency issues).

Qualifications & Skills:

• 6+ years of experience
• Master’s or PhD in a relevant field (Computer Science, Software Engineering,  Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML
• LLM & GenAI Mastery: Expert in building and deploying LLM-based applications using RAG, prompt engineering, and vector databases. Skilled in LLMOps tools (LangChain, LlamaIndex) and fine-tuning models for enterprise use, including agent-based architectures.
• MLOps & Cloud Infrastructure: Proficient in cloud ML platforms (AWS, GCP, Azure) and MLOps workflows. Uses Docker, Kubernetes, and IaC tools (Terraform, CloudFormation) for scalable deployments. Experienced in CI/CD, real-time inference, GPU optimization, and ML observability (Prometheus, Grafana, MLflow).
• Full-Stack Development: Capable of building end-to-end AI solutions, from front-end (React) to back-end APIs (Flask, FastAPI, Node.js). Skilled in integrating ML models with databases (SQL, NoSQL) and delivering seamless user experiences through robust software engineering.
• Proficient in Python (pandas, scikit-learn), deep learning (PyTorch/TensorFlow/Keras), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• Experienced with Snowflake-native ML (Snowpark Python, UDFs/UDTFs, Tasks/Streams).
• Competent in data engineering (SQL, ETL/pipelines, Spark/PySpark) and handling large structured/unstructured datasets.
• Strong understanding of AI/ML algorithms, application architecture, and design patterns.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications & Skills

• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on experience with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions, and feature management/registry tooling.
• Familiarity with fairness toolkits, XAI frameworks, and preparing models for validation, audit, or regulatory exams.
• Knowledge of SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment.
• Excellent written and verbal communication skills.
• Strong listening and teaching abilities.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Quick learner of new technologies.
• Self-directed with strong technology and communication skills.
• Ability to synthesize multiple sources of information and understand the broader operational context of the Bank.
• Collaborative team player with a practical and creative approach in a dynamic work environment.
• Ability to handle ambiguity, multitask, and adapt quickly to changing priorities.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

WHAT YOU'LL DO

As our customer base continues to grow with the excitement around BrazeAI, we’re expanding our team! Join our Forward-Deployed Data Scientist group of creative technical experts who partner with customers to ensure their success. In this role, you will:

• Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
• Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
• Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success

WHO YOU ARE

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions
• Nice-to-have skills: Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL, and pipeline optimization, or reinforcement learning algorithms
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value
• Entrepreneurial problem-solver: You identify opportunities and risks early, troubleshoot obstacles, and drive creative solutions
• Continuous learner: You stay current with industry trends, explore new tools/technologies, and thrive in environments that push you to grow
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $98,000-$164,000/year, with an expected On Target Earnings (OTE) between $109,000-$183,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

#LI-Hybrid

Hi, we're Oscar. We're hiring a Senior Analyst, Data Analytics, SIU to join our SIU 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:

The Senior Analyst, Data Analytics, SIU partners across the organization to manage inefficiencies in the business. You will support teams in scoping, analyzing and monitoring performance of important financial and utilization metrics in service of our goals. The Senior Analyst, Data Analytics collaborates independently with stakeholders to define key questions and scope analyses. They may at times be called upon to speak to prepared analysis both internally and externally. This work aims to reduce medical waste and deliver more affordable and higher-quality health care for Oscar's members.

You will report into the Manager, SIU Data Analytics & Reporting.

Work Location: This is a remote position, open to candidates who reside in: Arizona, Florida, Georgia, Illinois, Iowa, Kansas, Michigan, Missouri, Nebraska, New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Texas and Virginia. 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.

If you live within commutable distance to our New York City office (in Hudson Square) or our Tempe office (off the 101 at University Ave), you will be expected to come into the office at least three days each week. Otherwise, this is a remote / work-from-home role.  Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. 

Pay Transparency: The base pay for this role in the states of New Jersey and New York is: $86,628 - $109,761 per year. The base pay for this role in all other locations is: $75,265 - $98,785 per year.  You are also eligible for employee benefits, participation in Oscar's unlimited vacation program and annual performance bonuses.

You must be currently authorized to work in the United States on a full-time basis. Oscar will not sponsor applicants for this role.

Responsibilities:

• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues can understand, including packaging and presenting findings in a clear, concise and compelling manner
• Oversee the creation and maintenance of essential operational and analytical dashboards, and update and enhance them as our user's needs evolve
• Create models and tools that produce relevant insights to identify inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization 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:

• 1+ years of technical work experience using analytical tools and writing analytical reports
• 1+ 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 experience on at least 2 reporting projects requiring communication between technical and non-technical users
• 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
• Proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, finance or the insurance industry

Bonus points:

• 1+ years experience in preparing healthcare analytics and reporting
• 1+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO)
• 1+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

As a Hunter Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Work directly with prospective, greenfield, customers on their 0 to 1 journey with Databricks 
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems at scale 
• Comfortable programming in, and debugging, Python and SQL
• Experience using agentic coding harnesses and demonstrable experience scaling your work leveraging them 
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

About the Position

We are looking for a Data Engineer to turn messy, real-world datasets into reliable inputs for research and trading. Jane Street depends on data from a wide variety of sources to understand markets and the global economy—think world news, decades of weather patterns, deidentified credit card spending, or packet captures of stock exchange market data feeds. Clean, well-structured data is the difference between noise and a profitable trading signal. 

You'll work closely with trading desks to identify Jane Street's data needs, evaluate datasets, and build pipelines that ingest and transform external data. You'll figure out what data means and how best to represent it. We build our own tools and software when needed, so you'll also help shape the systems you use every day.

This is a collaborative role, but you'll own your work from end to end. It requires a mix of engineering, data analysis, and product sense. You'll develop deep expertise in your data domains and use that understanding to decide what's worth building next.

About You

• Have strong programming skills in any language (Python a plus); you write clear, correct, and maintainable code
• Proficient with SQL or DataFrame libraries like pandas or Polars
• Intellectually curious with a meticulous approach to data investigation; you enjoy the detective work required to make sense of unfamiliar datasets
• A clear and concise communicator

Prior experience with financial data is helpful but not required. We’re happy to hire talented engineers and teach them what they need to know.

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

Spring & Bond, a part of Real Chemistry,  is a digital media agency and consultancy helping pharmaceutical and medical device manufacturers build robust, omnichannel-enabled media executions for both HCP and consumer audiences. Our focus is on client empowerment through services like customer journey planning, media strategy & activation, technology evaluation, in-house capability development, and training.

We are looking for a Senior Data Engineer to help drive the design, build, and scale of our data infrastructure. This role will be responsible for architecting and maintaining multi-cloud data platforms, optimizing ETL pipelines, and ensuring data quality and availability across the organization. As a senior member of the Data Engineering team, you will not only deliver hands-on technical solutions but also mentor junior engineers, guide best practices, and help shape the direction of our data engineering capabilities.

What you'll do:

• Architect and optimize robust, scalable ETL pipelines and workflows to ingest, transform, and deliver data from multiple sources.

• Ensure data integrity and governance through validation frameworks, schema design, and proactive monitoring.

• Leverage advanced SQL and programming skills to extract, transform, and analyze data efficiently.

• Develop automation using Python, Pandas, AWS Lambda, and related tools to improve operational efficiency.

• Design and manage data platforms, including Snowflake, Athena, Redshift, BigQuery, and other cloud-based solutions.

• Collaborate cross-functionally with analysts, strategists, and business leaders to translate business requirements into technical solutions.

• Mentor and coach junior data engineers, setting standards for code quality, documentation, and best practices.

• Lead vendor and partner integrations, ensuring seamless data delivery and alignment with internal standards.

• Communicate effectively with both technical and non-technical stakeholders, providing clear insight and direction.

• Drive innovation, identifying opportunities to improve performance, scalability, and usability of our data systems.

What you should have:

• Bachelor’s degree in Computer Science, Data Engineering, or related field—or equivalent experience.

• 5–7+ years of experience in data engineering, with proven success building and scaling data systems.

• Expert knowledge of SQL and Python, including performance optimization and data manipulation libraries (e.g., Pandas).

• Strong experience with AWS data products (S3, Redshift, Athena, Lambda) and familiarity with multi-cloud environments.

• Deep understanding of data modeling, schema design, and best practices for large-scale data solutions.

• Demonstrated ability to design secure, reliable pipelines and troubleshoot complex issues.

• Experience leading projects and mentoring other engineers.

• Excellent communication, critical thinking, and problem-solving skills.

• Comfortable managing multiple priorities and delivering in a fast-paced environment.

Great-to-Haves

• Experience with data transformation and productivity tools (dbt, Jinja, etc.).

• Familiarity with Snowflake (Notebooks, Worksheets, VS Code plugin).

• Knowledge of data visualization platforms such as Looker Studio or similar BI tools.

• Exposure to digital marketing analytics and measurement frameworks.

Pay Range: $120,000-$137,750
This is the pay range the Company believes it will pay for this position at the time of this posting.  Consistent with applicable law, compensation will be determined based on job-related, non-discriminatory factors including but not limited to work experience, skills, certifications, and geographical location. The Company reserves the right to modify this pay range at any time. 

WHAT YOU'LL DO

• Use robust software engineering best practices to design, implement, and improve modular components in a cutting-edge product
• Collaborate closely with other teams (e.g., UI/UX, Product, Research, Implementation) to create scalable and dynamic Braze product components 
• Apply your extensive knowledge of TypeScript, JavaScript and their ecosystem to build a clean, reliable, and extensible user interface for the web
• Influence Braze’s product strategy and roadmap
• Support teams implementing Braze for customers to ensure their success
• Tech stack:
  • Web: TypeScript, JavaScript, Vue.js (v3) and its ecosystem (VueCLI with webpack), Node.js, Strapi, PostgreSQL, HTML5, CSS3
  • Data Science/ML Pipeline: Python (Pandas, TF, Fast API, Great Expectations), SQL (not required for this role although some experience with Python would be helpful)
  • We write well-tested, type-hinted, documented, modular code and use pre-commit hooks, CI/CD, and issue tracking for development

WHO YOU ARE

• Exceptional coder: you write clean code and you care about good design and development best practices
• Tinkerer: you regularly explore and learn new technologies and methods
• Problem solver: you recognize patterns, synthesize information and come up with creative, simple, and practical solutions
• Entrepreneurial: you proactively identify opportunities and risks, work around obstacles, and always seek creative ways to improve processes and outcomes
• Structured and organized: you can structure a plan, align stakeholders, and see it through to execution
• Clear communicator: you are able to express yourself clearly and persuasively, both in writing and speech

For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $129,600 and $232,200/year with an expected On Target Earnings (OTE) between $144,000 and $258,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

About the Position 

As a Data Scientist on the platform prediction team, you'll translate our probability of success predictions into measurable portfolio-level outcomes. You'll architect core systems — order management, execution simulation, portfolio construction, risk monitoring, and performance attribution — that let us rigorously evaluate signals from our AI-driven predictions in public and private equities and our internal portfolio.

This role sits at the intersection of quantitative finance, healthcare data, and AI-driven drug development. If you're excited about applying portfolio construction and risk management fundamentals to one of the most consequential prediction problems in healthcare, this is the role.No other company — hedge fund or pharma — has a technical data science position translating drug development experience into durable AI-native portfolio strategies. The skills you develop here — portfolio construction over assets with radically asymmetric risk profiles, clinical trial analytics, AI/ML in production, and risk management across multi-year horizons — can directly impact the delivery of new and effective therapeutics to patients by best aligning impactful medicines with economic incentives.

Responsibilities

• Work with the team to implement and maintain core portfolio engine: order management system, execution simulation layer, portfolio construction service, and performance tracking
• Design risk frameworks that quantify exposure across a portfolio of drug development bets with radically different risk profiles, timelines, and failure modes
• Run rigorous backtesting experiments with strict temporal constraints to evaluate Formation strategies against baseline approaches and measure marginal signal from new evidence sources
• Coordinate across the organization to integrate internal Formation data sources (clinical trial data, genomic evidence, real-world data) and proprietary tooling into portfolio analytics pipelines
• Work with product and engineering teams to build dashboards and reporting that communicate portfolio performance, risk metrics, and strategy comparisons to both technical and executive stakeholders
• Collaborate with the broader data science team to ensure portfolio-level evaluation feeds back into model improvement and evidence prioritization

About You 

Required Qualifications

• MS or PhD in a quantitative field (statistics, finance, physics, computational science, engineering, or related)
• 1-3 years in a quantitative research, data science, or analytics role — finance, healthcare, academic research, or consulting all count; substantive internships qualify
• Strong Python programming skills with experience in data-intensive workflows (pandas, numpy, scipy)
• Solid grasp of core portfolio construction and risk concepts: position sizing, rebalancing, Sharpe ratio, drawdown, volatility, benchmark comparison
• Demonstrated ability to work with messy, real-world datasets — comfortable with data wrangling, deduplication, and quality assessment
• Clear communicator who can present quantitative results to both technical peers and business stakeholders

Preferred Qualifications

• Experience with backtesting frameworks or portfolio simulation (vectorbt, Backtrader, or custom implementations)
• Exposure to healthcare, pharma, or biotech data (clinical trials, claims data, -omics, real-world evidence)
• Familiarity with alternative data in a research or investment context
• Experience with probability-of-success modeling, drug development decision analysis, or health economics
• Comfort with LLMs or AI/ML pipelines in a production or research setting
• Familiarity with dashboard/visualization tools (Streamlit, Plotly, Dash) and pipeline orchestration (Dagster, Airflow)

Healthcare OR finance domain knowledge is valued; both are not required.

Total Compensation Range: $154,500 - $202,000

Market Operations Specialist - Options

About IEX:

IEX (IEX Group, Inc.) is an exchange operator and technology company dedicated to innovating for performance in capital markets. Founded in 2012, IEX launched a new kind of securities exchange in 2016 that combines a transparent business model and unique architecture designed to protect investors. Today, IEX applies its proprietary technology and experience to drive performance across asset classes, serve investors, and advocate for transparent and competitive markets.

The Market Operations Team:

IEX is looking for a driven, motivated early-career candidate to join our Market Operations desk. You will have familiarity with U.S. options market structure, programming & automation, data analysis, and the support of multifaceted technology systems. You will demonstrate the composure and aptitude required to work effectively in a dynamic, high-pressure trading environment.

This position is best suited for a highly collaborative, team-oriented individual who is passionate about working with technology, trading systems, and data. You’ll work directly with other industry participants to expand access and understanding of the IEX market as well as cross functionally with IEX’s product, technology, and regulatory teams.

ABOUT YOU:

• Excellent verbal and written communication skills
• Superlative attention to detail
• Keen interest in technology and desire to grow skills in this area
• Open-minded and able to quickly acquire new concepts and ideas
• Self-motivated and comfortable with independently driven work
• Availability and commitment to accommodate a flexible work schedule and an on-call environment

WHAT YOU WILL DO:

• Execute and maintain daily operational procedures
• Develop expertise with IEX systems, market functionality, order types and external interfaces
• Design, build, and maintain automation scripts owned by the Market Operations team
• Perform data analysis to support troubleshooting client issues, improving operational efficiency, and managing risk
• Participation in general IEX product development and business development initiatives
• Collaborate with internal teams at IEX – including Technology Operations, Product Management, Business Development, Business Analytics, Quality Assurance, Compliance, and Regulation
• Participation in industry tests

YOUR BACKGROUND:

• Bachelor's degree or equivalent combination of education and experience
• Microsoft Excel experience – ability to create pivot tables and fluency in using functions.
• Python programming experience – creating scripts to automate tasks and work processes and always seeking to improve the code and functions where possible.
• Data analysis experience – spent time with a data science module like Pandas for Python or a query language like KDB+/Q or SQL (we love Jupyter notebooks!). You enjoy spending time with large datasets and using your skills to create interesting views.
• Ability to acquire applicable certifications within 90 days of hiring

NICE TO HAVES:

• Operational experience on a trading / operations desk
• Familiarity with electronic trading, trading systems, and options market structure a plus
• Familiarity with a versioning system like Git
• Familiarity with an automation scheduling tool like Rundeck
• Knowledge of micro-market structure, order types, and order book behavior

Our job titles may span more than one career level. The starting annual base pay is between $85,000 and $110,000 for this NY-based position. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The annual base pay range is subject to change and may be modified in the future. This role is eligible for bonus and equity.

Here at IEX, we are dedicated to an inclusive workplace and culture. We are an Equal Opportunity Employer that does not discriminate on the basis of actual or perceived race, color, creed, religion, alienage or national origin, ancestry, citizenship status, age, disability or handicap, sex, marital status, veteran status, sexual orientation, genetic information or any other characteristic protected by applicable federal, state or local laws. This policy not only complies with all applicable laws and protects workers' rights but is vital to IEX’s overall mission and values.

NYC Applicants_Notice Regarding Use of Automated Employment Decision

Quantitative research is a key driver of innovation at CTC and one of the pillars upon which our firm is built. We are seeking a Quantitative Researcher to partner with Trading and Technology to strengthen, scale, and evolve the firm's trading capabilities within one of the quant research teams. As a Quantitative Researcher, you will be embedded on a research desk, working close to the tip of the spear in a dynamic environment. This includes 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 the Quant team at CTC! 

What You’ll Do

• 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 
• Conduct independent, high quality research in quantitative finance 
• Communicate complex ideas and research results effectively, both in writing and verbally 
• Drive innovation and results through analytical prowess and business acumen 

What We’re Looking For

• PhD in Science or Engineering fields (e.g. Statistics, Mathematics, Physics, Applied Mathematics, Operations Research, Electrical Engineering) strongly preferred 
• Minimum 5 years of experience as a Quantitative Researcher in a top systematic trading team 
• Demonstrable track record of generating positive PnL 
• Advanced programming skills and experience with the software development lifecycle 
• Proven ability to blend academic rigor with practical application in fast-paced trading environments 
• Unwavering commitment to quality, coupled with a drive for delivering commercial outcomes 
• Python skills including Numpy and Pandas libraries 

Nice to Haves

• Experience with a wide variety of market and alternative data  
• Expertise in US options markets, options pricing models, volatility surfaces, and risk management techniques  
• Strong track record of publications in an industry setting 

Data at Brex

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

What you’ll do

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

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

Where you’ll work

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

Responsibilities

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

Requirements

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

Bonus points

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

Compensation

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

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

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 Data Analyst II (DA), you will play a central role in enhancing the operational tracking and reporting capabilities of different business teams across Brex. You will work closely with Data Scientists, Data Engineers, and partner teams to drive meaningful insights for the business through visualizations, self-service tools, and ad-hoc analyses. This is a high-impact role in a fast-paced fintech environment where your work will directly influence strategic decisions.

Where you’ll work

This role will be based in our São Paulo 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

• Apply data visualization and storytelling skills in creating business intelligence solutions (such as Looker and/or Hex dashboards) that enable actionable insights.
• Perform ad-hoc analyses and deep dives to investigate business questions, surface trends, and provide data-driven recommendations.
• Develop self-service data tools and processes that empower business stakeholders to independently monitor the performance and health of their respective areas.
• Collaborate closely with Data Scientists and Data Engineers to identify data sources, enable data pipelines, and support the development of analytical data models that operationalize reports and dashboards.
• Implement and maintain rigorous data quality checks to ensure the integrity and robustness of datasets used across dashboards, reports, and analyses.
• Partner with various departments—including Sales, Operations, Product, and Finance—to understand their data needs and deliver tailored analyses and reporting that support strategic planning.
• Contribute to the automation of recurring analyses and reporting workflows using Python.

Requirements

• 4+ years of experience in data analytics or a related role in a professional setting.
• 3+ years of experience working directly with Sales, Operations, Product, or equivalent business teams.
• Fluency in SQL to manipulate data and perform complex analyses (CTEs, window functions, joins across large datasets).
• Proficiency in Python for data analysis, automation, and scripting (Pandas, NumPy, and similar libraries).
• Experience with business intelligence and data visualization tools (Looker, Hex, Tableau, or similar).
• Strong quantitative and analytical skills with a demonstrated ability to translate data into business insights.
• Strong communication skills and the ability to work effectively with stakeholders across different functions and levels of technical fluency.
• 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

• Familiarity with cloud data platforms (e.g., Snowflake, BigQuery, Databricks).
• Familiarity with dbt for data modeling and transformation.
• Exposure to data pipeline orchestration tools (e.g., Airflow).
• Experience in fintech, financial services, or payments.
• Comfort operating in a fast-paced, high-growth environment with evolving priorities.

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

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.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As a Senior Value Engineer specializing in Healthcare Distribution and Logistics, you are pushing the envelope in solving business-critical problems for one of the world's largest healthcare wholesale and distribution enterprises. You will be working intimately with this strategic client, understanding their uniquely complex objectives—spanning from high-volume warehouse optimization and pharmacy fulfillment to ensuring seamless hospital supply logistics and DSCSA compliance—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners (e.g., Microsoft, OpenAI, Databricks).

  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the intricate realities of our customer's massive, high-velocity distribution network. This enables them to industrialize AI, unlocking real ROI on deployments at scale, and ultimately ensuring critical medicines and medical supplies reach care providers and patients without delay. There is no AI without PI. You will prototype these solutions, demonstrate their value to global Supply Chain SVPs and logistics leaders, and ensure successful implementation, adoption, and value realization to solidify and expand the footprint of Celonis within this premier healthcare distribution network.

Key Responsibilities:

• AI Discovery & Solutioning: Understand the client's overarching AI strategy and the distinct supply chain challenges inherent to healthcare wholesale (e.g., predictive demand forecasting for generic and brand pharmaceuticals, optimizing distribution center throughput, navigating complex contract pricing, or managing acute care logistics). As a Celonis product and distribution domain expert, translate these high-volume logistics requirements into innovative AI solutions that drive measurable impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the expansion/pre-sales cycle across various distribution and operational business units. Remain deeply involved post-sale to guide implementation, ensuring agreed value, efficiency, and adoption thresholds are successfully reached in both corporate and warehouse environments.

• Hackathons & Prototyping: Think out of the box with a "can-do" attitude, tackling heavily siloed legacy logistics and fulfillment networks. Leverage cutting-edge AI technologies to rapidly build creative prototypes in client hackathons, solving critical pain points across inventory allocation, fleet routing, procurement, and customer service.

• Agentic Process Transformation: Support the client in achieving tangible ROI from AI at an enterprise scale. Enable a fundamental shift from traditional, rule-based automation to autonomous AI agents empowered by the Celonis Process Intelligence Platform (e.g., autonomous resolution of order-to-cash disputes, intelligent backorder handling, or automated warehouse exception management).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. Architect and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, ensuring seamless integration with complex enterprise ERPs, Warehouse Management Systems (WMS), Transportation Management Systems (TMS), and strict regulatory track-and-trace frameworks (e.g., DSCSA).

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for Healthcare Distribution, scaling knowledge across the organization regarding the nuances of medical/surgical and pharmaceutical wholesale operations.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within highly complex Supply Chain, Logistics, or Wholesale Distribution environments (Healthcare/Pharma distribution preferred). This includes defining AI roadmaps, building compelling ROI/TCO business cases for large-scale distribution networks, and guiding technical implementations through to value realization.

• Deep understanding of supply chain business processes native to high-volume distribution (such as Order-to-Cash, Procure-to-Pay, Inventory Management, Warehouse Operations, or Transportation Logistics) with the ability to translate high-level operational needs into specific AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent chatbots for pharmacy/hospital customer support, or automated extraction of data from complex vendor contracts and rebate agreements).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies for handling massive, high-velocity transactional supply chain datasets.

• Strong presentation skills to both internal and external stakeholders (including supply chain executives, warehouse directors, and enterprise IT leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, supply chain management, logistics, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations suited for highly regulated healthcare logistics environments.

• Familiarity with distribution-specific systems and standards (e.g., Manhattan, Blue Yonder, SAP EWM, and DSCSA track-and-trace serialization data).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As a Senior Value Engineer specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As a Senior Value Engineering Consultant specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

IMC is looking for a Quantitative Developer to own the full path from research to production. This role blends research and engineering, with tight feedback loops from ideation to live trading. You will build the systems that turn quantitative insights into measurable edge, with direct visibility into how your work creates impact.

Your Core Responsibilities

• Build and maintain systems that span research and production, enabling rapid iteration from idea to production
• Design high-fidelity simulation and backtesting infrastructure that models latency, microstructure, and real-world constraints
• Define, compute, and curate features across instruments, regimes, and time horizons
• Own feature and signal pipelines, ensuring clean, consistent delivery from research to execution
• Contribute to strategy optimization, balancing expected performance with real-world constraints
• Debug issues end-to-end across research and execution

Your Skills and Experience

• 3-7 years of experience in quantitative software development, preferably at a trading firm or systematic fund
• Strong production experience in Python and C++, including data analysis workflows (pandas, polars, or similar)
• Strong grounding in probability, statistics, and time series analysis; familiarity with backtesting and simulation frameworks
• Solid understanding of ML concepts as applied to systematic strategies, from research through production
• Experience with low-latency systems is valuable
• Ability to work fluidly across research and engineering teams

Role Description

• As an Senior Value Engineer specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.

Who We're Looking For

As a Senior Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.

You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.

With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.

Note: Due to the nature of our aerospace and defense work, this position is open to US citizens only.

This Role 

As a Senior MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.

You'll:

• Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments.
• Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence.
• Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars.
• Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others.
• Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure.
• Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
• Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX.

As a senior member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.

Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!

What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

And it doesn’t stop there …

🚀 Equity options - share meaningfully in the company you’re helping to build.

💰 5% contribution to 401(k) - build long-term security with a strong retirement plan.

🍽️ Free team lunch 1x/week - good food, great company, and space to connect.

🏥 Private health insurance – comprehensive cover for you, offering total peace of mind.

👶 Enhanced parental leave – 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.

☀️ 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.

📈 Personal development – dedicated support for learning, development, and leveling up over time.

💪 Gympass / Wellhub (subsidized) – for you and up to 3 family members, supporting both physical and mental wellbeing.

💳 Flexible Spending Account (FSA) – set aside pre-tax dollars for eligible healthcare expenses.

🔎 Watch this space, we’re continuing to build this as we grow…

Salary range:

$200,000 - $250,000 depending on experience 
Seniority will be assessed throughout our interview process 

About the Role

The Data & Analytics team is dedicated to building innovative data products that provide actionable insights, empowering our partners to succeed. We focus on curating and maintaining key data sources and statistics that serve both internal and external stakeholders.

What You'll Do

Advanced Engineering & Coding

• End-to-End Ownership: Own the full lifecycle of data products, from initial conceptualization and architecture through to production deployment, optimization, and maintenance.
• Core Development: Design and code complex dbt models and data transformation logic for high-volume financial datasets (e.g., trade transactions, stock ledgers, and clearing/settlement records).
• Python Automation: Write production-grade Python scripts for advanced data processing, anomaly detection, and custom orchestration logic that SQL cannot handle alone.
• Performance Engineering: Take ownership of the "hardest problems" regarding query performance. Refactor legacy code and optimize incremental loading strategies to reduce costs and latency at scale.

Technical Architecture & Standards

• CI/CD & DevOps: Own the technical implementation of our data deployment reporting pipelines (Git, dbt Cloud), ensuring robust version control and seamless integration.
• Data Quality as Code: Engineer automated testing frameworks and validation suites (using dbt tests/Python) to ensure data integrity for critical business layers.

Leadership & Cross-Functional Impact

• Technical Project Leadership: Act as the hands-on lead for major initiatives. Scope, design, and manage complex data projects while remaining active in the codebase to ensure high-quality delivery.
• Cross-Functional Partnership: Partner directly with stakeholders across Product, Finance, Operations, Risk, and Trading to translate domain-specific requirements into robust data products and reporting solutions.
• Mentorship & Guidance: Act as the "go-to" technical resource for the team. Conduct thorough code reviews and help senior and junior engineers solve blockers through pair programming and architectural guidance.

What You’ll Need

• 8+ years of professional experience in analytics engineering or data engineering, with a proven track record of building and scaling analytical data ecosystems.
• Expert proficiency in SQL, with experience optimizing complex queries and data models at scale.
• Advanced proficiency in Python for data manipulation (Pandas/Polars/Spark) and interaction with APIs/AWS services.
• Experience using Databricks for analytics workloads, including building and optimizing data models using Databricks SQL and dbt.
• Experience with dbt materializations, macros, and package management.
• Experience architecting data models for FinTech and Capital Markets, including trade lifecycles, clearing/settlement, risk models, and financial reporting.
• AI-Assisted Engineering: Proficiency in leveraging AI tools (e.g., GitHub Copilot,or similar LLMs) to accelerate code delivery, automate documentation, and optimize engineering workflows.
• Proven ability to build data solutions that are reusable and modular, rather than one-off scripts.
• Experience treating data as software by implementing unit testing, CI/CD, comprehensive documentation, and SLA monitoring.
• Ability to independently diagnose and resolve complex errors or issues within distributed systems (Spark/Databricks).
• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.

Special Knowledge (Nice to Have, But Not Required)

• Experience implementing Airflow or similar orchestrators.
• Experience with Sigma Computing (from a data modeling perspective).
• Experience building Data Apps within Databricks.
• Experience using AI/LLM tools to enable faster, smarter analytics workflows.

Work Authorization Requirement:

Applicants must be legally authorized to work in the United States on a full-time basis without the need for current or future employer sponsorship.  The company does not offer visa sponsorship, transfers, or immigration support for this role.

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Jump’s Client Market Making business provides clients with direct access to our liquidity across a wide range of asset classes in all market conditions. Leveraging our proprietary pricing platform, we deliver fully customizable and disclosed liquidity solutions designed to meet the unique needs of each of our clients.

As a Trading Services Specialist in our Client Market Making business, you will play a key role in onboarding clients, supporting global platform operations, and collaborating with business development, product, technology, and back-office teams to enhance the client experience.

This role is based in either Chicago, Illinois or New York, New York.

What You'll Do:

• Manage the entire client onboarding process including connectivity, session setup, conformance testing, and pilot trades.
• Monitor and resolve production issues to ensure a seamless client trading experience.
• Collaborate with developer and production reliability engineer teams to identify workflow and system issues, document/prioritize tickets, and deliver solutions.
• Partner with trading, product, and sales teams to turn client requests into actionable roadmap items.
• Create and maintain clear up-to-date documentation that enables team-wide knowledge sharing.

Skills You Need:

• Bachelor’s degree with demonstrated experience in a fast-paced, client-facing trading environment.
• 3 to 6 years of relevant experience working with trading systems, order entry protocols, market data protocols, troubleshooting technical issues and providing production support.
• Strong understanding of the client onboarding lifecycle, including FIX protocol, conformance testing, and network routing.
• Product expertise in at least one asset class (e.g., FX, CFDs, equities, fixed income).
• Proven ability to successfully lead and complete technical projects.
• Experience with data analysis using tools like Python (Pandas, NumPy), SQL, or KDB+.
• Flexibility to collaborate across time zones, including occasional off-hours work.

Benefits include:

• Private Medical, Vision and Dental Insurance
• Travel Medical Insurance
• Group Pension Scheme
• Group Life Assurance and Income Protection Schemes
• Paid Parental Leave
• Parking and Commuter Benefits