Quantitative Trader Developer Jobs

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else. As a PhD Quantitative Research Intern, you'll spend 10-12 weeks pointing the research skills you've spent years building at markets. You'll collaborate with researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious. This isn't an internship where you observe from the sidelines, or re-run someone else's experiment. Outstanding work has the potential to shape production strategies and generate real, measurable returns. Ideal candidates are researchers who want to see their methods meet live markets: mathematicians, physicists, statisticians and computer scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London. What You'll Work On You'll work on real research problems, not simulated exercises. Your work would include: Discovering predictive patterns from billions of market events Designing statistical models that identify trading opportunities Applying probability, optimization and machine learning to open research problems Running large-scale simulations and experiments on high-performance research infrastructure Designing experiments and backtests to evaluate hypotheses Building AI-powered research agents that accelerate experimentation Developing infrastructure for rapid, large-scale research Translating research into production-ready trading signals Exploring new ML, AI and quant finance techniques to find the next source of alpha What You'll Learn Beyond the technical exposure, you'll learn what changes when research meets live markets: why a result that would survive peer review can still fail as a trading signal, how costs and capacity constrain an idea that looks clean on paper, and how to tell a model that is right from one that is right for the wrong reason.

At Graviton, we don't believe the best trading strategies come from following established playbooks. They come from asking better questions. Why does a pattern exist? What is driving it? Is it real or just noise? Can it be explained, modelled and turned into an edge? As a Quantitative Researcher, you'll work on those questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies, working alongside researchers and technologists in an environment where an idea on a whiteboard can reach live trading quickly. This isn't a role where the answers are in a textbook. The problems are open-ended, the data is enormous, and finding the answers is the job. Ideal candidates are rigorous thinkers who genuinely enjoy mathematics, programming and figuring out things that aren't obvious, based in our Singapore, London, Amsterdam or US offices. What You'll Work On You'll work across quantitative research and systematic trading, taking ideas through the full lifecycle: question, hypothesis, experiment, model, validation, strategy, production. Depending on your team and research interests, your work would include: Discovering predictive patterns and sources of alpha from billions of market events Formulating hypotheses about market behaviour and designing experiments to test them Applying probability, statistics, optimization and machine learning to build predictive models and quantitative signals for systematic trading Designing robust backtests and statistical tests to distinguish genuine signals from noise Working with large and complex datasets to uncover patterns that aren't immediately visible Investigating market microstructure and how markets behave at different timescales Evaluating strategy performance, identifying weaknesses and continuously refining models Developing research infrastructure and AI-powered tools and agents that make experimentation faster and analysis deeper Working c

Quantitative Developer, Risk Technology A CAREER WITH POINT72’s TECHNOLOGY TEAM As Point72 reimagines the future of investing, our Technology team is constantly evolving our firm’s IT infrastructure and engineering capabilities, positioning us at the forefront of a rapidly evolving technology landscape. We’re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision making and enhance how we build and operate our platforms and applications. As a member of Point72’s Technology team, we encourage and support your professional development from day one—helping you advance your technical skills, contribute innovative ideas, and satisfy your own intellectual curiosity—all while delivering real business impact for our multi-billion-dollar global business. WHAT YOU’LL DO Collaborate with Risk quants to design new risk factor models and refine existing ones Develop quantitative risk and performance analytics to proactively anticipate and address stakeholder needs Build a scalable reporting framework capable of processing terabytes of data for complex risk calculations Collaborate with engineers on system design, code quality, and architecture decisions across the team's shared codebase Partner directly with risk, research and other internal teams to translate ambiguous business problems into technical requirements and solutions WHAT’S REQUIRED Strong understanding of equity factor models and their construction and application (e.g., MSCI Barra, Axioma, Bloomberg) Demonstrated track record and hands-on experience in financial instrument modeling, particularly within the equity space 5+ years of programming experience in Python or another language commonly used in quantitative and statis

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: Freddie Mac’s Single Family Division is currently seeking an analytical and curious model developer who has strong business knowledge in credit risk, preferably collateral. This Quantitative Analytics Tech Lead position will include collateral model development, analysis and support potentially including some ad hoc analysis and data work in addition to developing new models and methods of evaluating collateral. Our Impact: We are responsible for developing Single Family collateral models that streamline the loan origination process while improving our credit risk exposure. Your Impact: Developing analytical methods and models that assess the collateral value and risk of Single Family properties. Providing resolutions to an extensive range of complicated problems; solutions are innovative, thorough, and practicable Providing modeling and analytical support to a line of business or product area Working under limited direction, independently determining and developing approach to solutions. Qualifications: PhD in economics, finance, statistics, or related quantitative discipline with 3+ years' experience, or Master’s with 5+ years relevant experience. Business experience will be weighted more than academic degrees. Demonstrated expertise in credit risk modeling (preferable collateral modeling), with experience working with model users to understand the model and develop new modeling and analytics methods and ideas. Proficiency in o

Job Responsibilities A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. You will gain exposure to a variety of activities, which may include: Developing automated equities trading applications and real-time analytics Optimizing data ETL pipelines, persistent / in-memory caches and SQL databases Work alongside quant researchers developing quant signals. Improving signal research and trading tools infrastructure Desirable Candidates Undergraduate or higher degree in computer science, machine learning, or other quantitative discipline 5+ years of experience at a hedge fund, major investment bank, or quantitative trading firm Strong programming experience in Python with production-level coding quality Experience with containerization and orchestration technologies, particularly Docker Experience with Unix environment and shell scripting Knowledge of profiling (e.g. VisualVM, async-profiler) and code optimization is a plus Knowledge of statistics and machine learning is a plus Willing to take ownership of his/her work, working both independently and within a small team Prior experience in the financial services industry is a plus Commitment to the highest ethical standards

JOB RESPONSIBILITIES A highly collaborative, fast-growing team, Point72 Internal Alpha Capture (IAC) is developing scalable quantitative equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, a broad range of public and proprietary data sources, and unparalleled computing power. You will gain exposure to a variety of activities, which may include: Developing automated equities trading applications and real-time analytics Optimizing data ETL pipelines, persistent / in-memory caches and SQL databases Work alongside quant researchers developing quant signals. Improving signal research and trading tools infrastructure DESIRABLE CANDIDATES Undergraduate or higher degree in computer science, machine learning, or other quantitative discipline 5+ years of experience at a hedge fund, major investment bank, or quantitative trading firm Strong programming experience in Python with production-level coding quality Experience with containerization and orchestration technologies, particularly Docker Experience with Unix environment and shell scripting Knowledge of profiling (e.g. VisualVM, async-profiler) and code optimization is a plus Knowledge of statistics and machine learning is a plus Willing to take ownership of his/her work, working both independently and within a small team Prior experience in the financial services industry is a plus Commitment to the highest ethical standards

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: We are seeking a Quantitative Risk Analysis, Associate II to join the Credit Analytics & Reporting team in the Single-Family division. This position will be tasked with developing deep understanding of data and current code, designing analytical approaches for business questions and scenario evaluations, managing data research, analyses and preparation of reports and presentations. Our Impact: Our team is responsible for producing reporting packages to monitor trends and performance. We analyze different test and learn or pilot programs to assess risk of the offerings and create reports to monitor these offerings closely to assess broad roll out. We perform significant user activities for different enterprise models for user acceptance testing and provide feedback. Your Impact: Implement baseline processes and reports monthly and interpret results as it relates to credit risk management. Follow appropriate controls and standards established to maintain and build documentation for processes & reports. Participate in performing ad-hoc analytics in support of credit policy. Cleanse, manipulate and analyze large datasets using statistical software. Collaborate with team members and interact across organizational lines to meet business objectives. Qualifications: Bachelor's Degree in Statistics, Economics, Finance, Mathematics, Computer Science, Data Science or related field, advanced Degree is a plus Minimum 1-3 years of releva

Position Overview At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success. As a Quantitative Analytics and Modeling Consultant Senior Validator within PNC's Model Risk Management organization, you can be based in Pittsburgh, PA / New York City / Tysons Corner, VA. We are seeking a Senior Validator to join PNC’s Model Risk Management team within Independent Risk Management. As a senior validator, you will perform rigorous independent reviews of PNC’s Capital Markets models, including derivatives pricing models, Value-at-Risk (VaR) models, and counterparty credit risk models, such as Potential Future Exposure (PFE), Credit Valuation Adjustment (CVA), and Funding Valuation Adjustment (FVA), and related interest rate and term structure models used in pricing and risk measurement. Key Responsibilities: 1. Independent Model Review: Perform qualitative and quantitative assessments of all aspects of models including data quality and integrity, theoretical assumptions and methodologies, and performance testing; Specific respons

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: The Quantitative Analytics Director is a strategic analytics leader responsible for transforming complex data into actionable business insights for senior executives and key stakeholders. This role emphasizes insight generation, decision support, and business impact while requiring strong fluency in quantitative methods, large-scale data analysis, and advanced analytical techniques. The Director will lead the development and implementation of analytical workflows that accelerate insight creation, improve analytical efficiency, and enhance decision-making. A critical responsibility of the role is ensuring these AI capabilities are developed, governed, and deployed in a controlled, transparent, and compliant manner. This position leads a team of analysts and data scientists and serves as a key partner across business, risk, technology, and analytics functions. Our Impact: Our team plays a critical role in helping Freddie Mac understand, anticipate, and manage credit risk across a dynamic mortgage market. By bringing together deep insights on how credit risk intersects with other aspects of our business, we provide timely insights that inform business decisions, strengthens governance, and supports the company’s mission. This is a role with opportunities to shape frameworks, influence cross-divisional outcomes, and engage with senior leaders on issues that matter to Credit Risk Management (CRM) as Freddie Mac balances credit risk and other scorecard items. Y

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: Are you curious and analytical? Do you thrive on working in a team environment? Are you looking for an inclusive company culture? Freddie Mac’s Single-Family Credit Analytics, Reporting and Decision Strategy group needs creative, forward-thinking individuals like you! We want to hire individuals who seek out complex business problems and develop viable solutions. The Quantitative Analytics Professional position is responsible for ensuring the reasonableness and consistency of statistical models, analytics and methodologies used in decision making in the Single Family guarantee business. Our Impact: Our team serves as the business user for multiple very high- and high-risk models. Our goal is to leverage all available models and tools to facilitate and optimize credit risk management and decision strategies. Our team is responsible for forecasting SF credit losses and enhancing company decision-making with respect to loan acquisition. Your Impact: SF (Single Family) model enhancement - oversight, documentation, and testing of new modeling frameworks Model tracking reports - reviewing and ensuring reports to SF Acquisition division are concise, complete, and transparent Mortgage modeling expertise - understanding default and prepayment modeling frameworks and providing insights Data quality - understanding data relationships and ensuring accuracy Testing and governance - assisting with UAT and model governance processes Qualifications: <

Quantitative Researcher Every trading strategy begins with a question worth answering. At Graviton, we believe the best trading strategies don't come from following established playbooks. They come from asking better questions. Why does a pattern exist? What is driving it? Is it real or just noise? Can it be explained, modelled and turned into an edge? As a Quantitative Researcher , you'll work on these questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies. You'll work alongside quantitative researchers and technologists in an environment where research moves quickly from an idea on a whiteboard to something that can influence live trading. The problems are open-ended. The data is enormous. The answers aren't in a textbook. You'll be expected to find them. What You'll Work On You'll work across different areas of quantitative research and systematic trading. Depending on your team and research interests, your work may include: Discovering predictive patterns and sources of alpha from billions of market events . Formulating hypotheses about market behaviour and designing experiments to test them. Applying probability, statistics, optimization and machine learning to complex research problems. Building predictive models and quantitative signals for systematic trading. Developing and improving research infrastructure that enables faster experimentation and deeper analysis. Working with large and complex datasets to uncover patterns that aren't immediately visible. Designing robust backtests and statistical tests to distinguish genuine signals from noise. Investigating market microstructure and understanding how markets behave at different timescales. Evaluating strategy performance, identifying weaknesses and continuously refining models. Working closely with technologists to translate research ideas into efficient, production-ready systems. Building AI-powered r

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the Capital Team The Capital team manages the financial foundation that supports Affirm’s lending and innovation. We lead the funding, liquidity, and risk management strategy across capital markets, treasury, deal structuring, analytics, and bank partnerships. The team secures efficient funding while supporting sustainable business growth. We balance cost, flexibility, and risk to ensure Affirm’s financial resilience through all economic cycles. By optimizing capital structure and managing liquidity, we help build a scalable and resilient financial platform. We’re looking for a smart, driven individual to join our Quantitative Markets team. The team is responsible for structuring and pricing Affirm’s debt funding deals, developing platforms and tools for optimizing funding strategies, and building models to analyze and predict the performance of Affirm’s consumer loans. The ideal candidate will have experience in structuring asset-backed transactions, working with rating agencies, and building quantitative models. Given the cross-functional nature of the role, the ideal candidate should have strong interpersonal and communication skills. What You’ll Do Work closely with the Capital Markets team to evaluate, structure and price consumer asset-backed transactions Develop and enhance capital structuring and pricing models tailored to Affirm’s consumer loan portfolio to enable efficient deal execution Build quantitative models to analyze and predict the performance of Affirm’s consumer loans Provide insights on capital markets deals to cross-functional teams for more optimal and efficient funding strategy and merchant pricing Partner cross-functionally with our Capital Markets, Treasury, Merchant Pricing, Credit, Commercial, Product and Engineering teams to evaluate funding, product

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About the Capital Team The Capital team manages the financial foundation that supports Affirm’s lending and innovation. We lead the funding, liquidity, and risk management strategy across capital markets, treasury, deal structuring, analytics, and bank partnerships. The team secures efficient funding while supporting sustainable business growth. We balance cost, flexibility, and risk to ensure Affirm’s financial resilience through all economic cycles. By optimizing capital structure and managing liquidity, we help build a scalable and resilient financial platform. We’re looking for a smart, driven individual to join our Quantitative Markets team. The team is responsible for structuring and pricing Affirm’s debt funding deals, developing platforms and tools for optimizing funding strategies, and building models to analyze and predict the performance of Affirm’s consumer loans. The ideal candidate will have experience in structuring asset-backed transactions, working with rating agencies, and building quantitative models. Given the cross-functional nature of the role, the ideal candidate should have strong interpersonal and communication skills. What You’ll Do Work closely with the Capital Markets team to evaluate, structure and price consumer asset-backed transactions Develop and enhance capital structuring and pricing models tailored to Affirm’s consumer loan portfolio to enable efficient deal execution Build quantitative models to analyze and predict the performance of Affirm’s consumer loans Provide insights on capital markets deals to cross-functional teams for more optimal and efficient funding strategy and merchant pricing Partner cross-functionally with our Capital Markets, Treasury, Merchant Pricing, Credit, Commercial, Product and Engineering teams to evaluate funding, product

Quantitative Insurance Solutions Analyst — Poznan, Poland. Apply via Workday.

Quant/Developer Analyst for a Discretionary Macro Investment Team focused on Structured Products A Career with Point72’s Macro Team Point72’s Global Macro business is a scaled, global investment platform with more than two decades of experience trading across rates, FX, credit, volatility, and emerging markets. Operating across 10 offices worldwide, we have doubled our capital allocation and grown our number of teams fivefold since 2020. We combine deep asset-class expertise with a highly collaborative culture across macro, fundamental equities, and systematic strategies to drive differentiated investment performance and support long-term career growth for our talent. What you’ll do Help architect and maintain the infrastructure for Structured Products investing. Leverage internal and external partners to help with data infrastructure builds. Integrate alternative and traditional data sets to help streamline our analytic processes. Use Artificial Intelligence (AI) to enhance and optimize processes. Work with risk parameters based on High Yield Equivalent and quantitative processes within market-standard analytics platforms such as Bloomberg. Manage and assist in special projects within the CLO market. What’s required 3+ years at a sell-side firm in a trading or quantitative research role, or as a quant at a buy-side credit or mortgage-focused fund. Undergraduate degree or higher in computer science, economics, engineering, mathematics, physics, or statistics. Advanced knowledge of a programming language such as Python, C++, or SQL. Advanced skills in Excel and cashflow modeling. Extensive experience with third-party structured credit cashflow engines (e.g., INTEX) and API. Commitment to the highest ethical standards. We take care of our people We invest in our people, their careers, their health, and their well-being. When you work here, we provide: Fully-paid health care benefits Generous parental and family leave policies Volunteer opportunities Support for employ