Quantitative Insurance Solutions Analyst Jobs

A Career with Point72's Trading Research Team WHAT YOU'LL DO Build and scale the research-to-trading platform that enables to support the design, testing, and deployment of quantitative strategies from prototype to production Design and implement high-performance analytics and pricing libraries in C++ and Python to support back testing, simulation, and real-time decision making Partner with investment professionals across the global business to translate ideas into robust, production-grade code and reproducible experiments Develop and maintain data pipelines and storage solutions that ingest, validate, and serve large historical and real-time market datasets Deploy, monitor, and operate production services, including automated testing, release processes, and incident response Drive performance and latency optimizations across code paths and infrastructure using profiling and benchmarking techniques Create tooling for experiment management, post-trade analysis, and model validation to measure strategy behavior and market impact Lead and contribute to the technical roadmap, increasing automation, resilience, and scalability of the research infrastructure Mentor junior developers, share best practices for software engineering, and promote a culture of continuous improvement and technical excellence WHAT'S REQUIRED Bachelor’s degree or higher in computer science, engineering, mathematics, physics, or a related quantitative discipline 3+ years of professional software engineering experience building production systems in a collaborative environment Strong proficiency in Python for data analysis and tooling and fluency in modern C++ for performance-sensitive components Practical experience building and querying relational databases or columnar data stores using SQL and hands-on experience with Linux development Proven experience designing and operating production services, including testing, deployment, and monitoring practices Demonstrated ability to profile, debug, and

ABOUT CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. WHAT YOU'LL DO The Quant Developer will be responsible for building and maintaining the research infrastructure and backtesting frameworks that support quantitative research, working closely with researchers to translate research ideas into robust, scalable, and maintainable research systems. The role spans multiple areas, including system design, data pipeline development, and the development of research and backtesting frameworks. WHAT'S REQUIRED Background in Electrical Engineering, Computer Science, or a related field, with 3+ years of software development experience as a software engineer. Strong programming ability in C++ and Python. Solid command of CI/CD practices and tooling, with the ability to design and maintain automated testing and build pipelines for research and backtesting environments. Practical knowledge and hands-on experience with distributed computing and distributed job scheduling / task assignment. Excellent analytical and engineering problem-solving skills. Demonstrated ability to work independently on large datasets and large codebases. A strong team player who works closely with researchers to translate research ideas into stable, maintainable research systems. Willingness to take ownership of your work, able to operate both independently and within a small team, while remaining careful, detail-oriented, and capable of performing well under pressure. Strong English communication skills. 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 provid

ROLE/RESPONSIBILTIES: We are seeking a quant research intern to join an NLP quant team within Point72. We believe the significant advances in NLP methods show promise for finance. We develop and launch end-to-end signals, from data processing to performance testing. The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading. Responsibilities may include: Using NLP to construct features from varied datasets Formulating research hypotheses to derive alpha Building and testing the performance of trading signals based on NLP and financial features Launching identified signals into production REQUIREMENTS: Bachelor’s, Master’s or PhD candidate in computer science or other quantitative discipline Proficient in Python and general software engineering principles (github, testing, dev workflow) Strong understanding of machine learning and statistics Prior research experience preferred Experience with deep learning, specifically NLP (PyTorch, HuggingFace, LLMs, etc.) preferred Data science stack familiarity preferred An interest in financial markets Great attitude A collaborative mindset Commitment to the highest ethical standards ABOUT POINT72: Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.

About Cubist: Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. About our Team: KEPL is a fast-growing team at Cubist Systematic Strategies. We are specialized in medium-frequency statistical arbitrage strategies with high Sharpe. The team is made up of people from top universities and top tier trading and tech firms, including: D.E. Shaw, Two Sigma, Citadel, Meta, Google, etc. We have an open and collaborative culture, and we value rigorous research and innovative technologies. Please send CVs to [email protected] with “2026 KEPL QD Application” in the subject line. Role: We are looking for a quantitative software developer to join our team and contribute to multiple initiatives that aim to expand our business. The candidate should be passionate about financial market, data and technology. In this team, the candidate will gain full-stack exposure and build expertise in multiple aspects of quantitative trading. Responsibilities: Improve data ETL pipeline and build tools to analyze new data efficiently. Build technologies to bolster research & trading efficiency. Expand to new markets and asset classes. Manage day-to-day operations in a fast-paced environment. Requirements Master/PhD degree in math, computer science, engineering, or other related fields. 1-3 years of professional experience in software development or data science/analytics. Strong combination of quantitative skills and programming skills. Proficiency in Python; knowledge of common data analytics tools (e.g., SQL, pandas) is a plus. Familiarity with the Linux environment. Excellent written and verbal communication skills. Willing to work in a fast-paced start-

JOB DESCRIPTION Point72 Asset Management is seeking a Quantitative Analyst to join its Portfolio Construction & Analytics Team (PCAT) in the Office of the CIO. PCAT’s mandate is to study all drivers of success for Long/Short Equities investment professionals using data, analytics, and models of investor behavior and the market. These analyses are shared with portfolio managers to improve their strategies and with senior management to better allocate capital across investment teams. The ideal candidate is a highly analytical and creative problem-solver who can conduct independent research, work effectively as part of a team, and effectively summarize and communicate findings. RESPONSIBILITES Conduct bottoms-up analysis on the firm’s portfolios to identify strengths and weaknesses in idea generation, trading, and construction Form top-down views on which strategies offer the best risk/reward for the firm Invent new analytics to quantify skill and frameworks to support trade-offs between different sources of skill and risk Quantify market drivers to support pre-trade risk taking and decision making Communicate key findings to the team, PMs, and Co-CIOs Learn to develop in and contribute back to shared code base, reports, and research tools DESIRABLE CANDIDATES 2 or more years of experience in a quantitative research, portfolio management, or risk management role dealing with equities or equities investments Undergraduate, MS or Ph.D. in Finance, Computer Science, Mathematics, Engineering, or Physics, or other quantitative discipline Experience with statistical models and essential methods of quantitative finance Some level of proficiency in quantitative programming (Python preferred) Highly analytical Good interpersonal skills Detail-oriented Self-starter Ability to work cooperatively in a team-oriented, fast-paced environment A commitment to the highest ethical standards and to act with professionalism and integrity Point72 is a leading global

Point72 is seeking a Quantitative Developer to join its Portfolio Construction and Analysis (PCA) team within the CIO office. ROLE Point72 is seeking a Quantitative Developer to join its Portfolio Construction and Analysis (PCA) team within the CIO office. The PCA team plays a vital role in the Equity L/S business at the firm, collaborating with investment teams to improve net revenue and risk adjusted returns. The Quantitative Developer will build, refine, and maintain an efficient technology infrastructure to enable and support the team’s quantitative research and analytical efforts. The ideal candidate is a smart, self-driven, and creative problem solver with strong technical and quantitative skills. RESPONSIBILITIES Architect, build, refine, and increase automation and robustness of the research infrastructure, including data access, risk modeling, and backtesting components Collaborate with quant researchers to implement framework for automating and presenting analytics, reports, and monitors Collaborate with firm-wide technology teams to deliver analytics and tools to users across the firm DESIREABLE CANDIDATES Undergraduate, Masters, or PhD in Computer Science or other quantitative discipline 3+ years of professional experience developing infrastructure to support an investment team Strong programming skills in Python and SQL Solid background in math/statistics/finance and familiarity with quantitative research methodologies and machine learning algorithms Understanding of and experience with the data ingestion process Ability to contribute to the analytics, quant research, and development process Understanding of portfolio construction is a plus Knowledge of equities is a plus High-energy personality and the ability to manage multiple tasks and deadlines in a fast-paced environment High degree of drive – must be a self-starter Ability to recognize and seize opportunities Depth of skills enabling him/her to perform ad hoc projects and task

Role Quantitative Researcher for a new team focused on systematic corporate bond and credit derivatives strategies. Responsibilities Independently conduct quantitative research, adopting a rigorous approach and using statistical and structural models Contribute to all aspects of the research and production process, including implementation of fitting tools; data organization; generation of alphas, risk and TC models; P&L attribution, etc. Proactively search for and prioritize new ideas and datasets for alpha potential Contribute to continuous improvement of the investment process and infrastructure in collaboration with the portfolio managers, developers and traders on the team Requirements PhD or Master’s degree in Economics, Finance, Statistics, Mathematics, Physics, or other quantitative discipline 2+ years of experience developing statistical and fundamental alpha signals, risk factors for single name credit, equities, or options. Demonstrated ability to conduct research utilizing large data sets Experience with FICC, credit or option pricing models is preferred Experience with numerical optimization methods is a plus Solid programming skills: understanding of the object-oriented programming and CI/CD framework. Proficiency in Python, including with packages used for data research, best practices of coding style, etc. ­ Strong communication skills Willingness to take ownership of his/her work, working both independently and within a team The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

ABOUT CUBIST: Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. RESPONSIBILITIES: Building components for both live trading and simulation Refining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting components Building tools for signal blending, simulation, portfolio construction, the research framework, and dashboards Maintaining and updating the platform, ensuring its stability, robustness, and security Developing robust data checking and storage procedures Troubleshooting and resolving any systems related issues and handle the release of code fixes and enhancements REQUIREMENTS: Bachelor’s degree or higher in computer science or other STEM discipline Advanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internals Experience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax) Proficiency with Linux Hands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control) Strong quantitative and analytical skills; command of linear algebra, statistics, and machine learning would be helpful Proficiency with C/C++ is a plus Experience with designing and implementing trading systems is a plus Commitment to the highest ethical standards

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role/Responsibilities: We are seeking a quantitative researcher for the Cubist Machine Learning Research group with experience in machine learning, especially recent deep learning and natural language processing technology. Researchers will use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave. Successful researchers manage all aspects of the research process including data ingestion and processing, data analysis, methodology selection, implementation and testing, prototyping, and performance evaluation. Researchers will be introduced to industry standard datasets, including understanding which data may be relevant to a certain model or financial problem; how to collect, parse, and clean the data; how to incorporate the data into innovative functional models; how to construct and develop features from raw data; and how to estimate effectiveness of such features. Researchers will also be provided with the opportunity to implement the full breadth of their knowledge and training to actively participate in all stages of research & development of financial models through use of machine learning. Based on experience from working with existing industry-standard models and algorithms, researchers will learn how to construct their own models in order to solve complex financial problems and enhance data prediction capabilities within the financial services industry. Requirements: PhD or PhD candidate in machine learning, computer science, statistics, or a related field Experience with sequential modeling and time

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 passionate about data? Are you curious and analytical? Do you thrive on working in a team environment? Freddie Mac’s Multifamily Portfolio and Risk Management team needs creative, forward-thinking individuals like you! We are seeking a Quantitative Analytics Professional who will be responsible for engaging the key Multifamily business partners to ensure the reasonableness and consistency of quantitative models, analytics and methodologies used in risk management and decision making in Multifamily business. Our Impact: We are the owners and developers of all major Multifamily credit, market risk and business decision models/tools. Our goal is to develop and apply all quantitative models and advanced data science tools to facilitate Multifamily risk management and optimize portfolio strategies. Our team is also responsible for Multifamily data analytics, regulatory capital, stress testing and business initiatives. This is an increasingly critical role given our focus on safety and soundness in multifamily business as well as the emerging risk management under the dynamical market environment. Your Impact: Lead efforts on data strategy, analytical tool design, and uses of Multifamily models; provide thoughtful inputs on development of Multifamily data, advanced analytics, and model assumptions/methodology. Lead best practices and improvement of Multifamily data management and analytical products to ensure adherence to industry standards and regulatory compliances. Collaborate with cross-functional teams to impl

About BlockTech BlockTech is a fast-paced algorithmic market maker at the frontier of global cryptocurrency derivatives and spot markets, expanding into new markets. We employ algorithms to trade our own capital, 24/7, across some of the most data-rich venues in finance. Crypto is one of the few markets where a researcher can still meaningfully move the edge. The data is abundant, the microstructure is novel, and the feedback loop between a research idea and live PnL could not be shorter. For the Summer of 2027, we're looking for a Quantitative Research Intern to join our Delta One team in Singapore. The role This is a 12-week summer internship at our Singapore office, giving you a unique opportunity to work on an end-to-end project with a real and direct business impact. You'll work in a small team and get the chance to understand how a trading firm actually works from the inside. Delta One is where we trade linear products: (perpetual) futures and spot. These are fast-moving, data-rich markets and a good place to see a research idea meet reality quickly. You will: Participate in a customized training program that will give you an understanding of financial markets in general, the company, and the project. Own a research project from design to deployment, guided by experienced Quantitative Researchers. Work with linear products and the data around them Understand how technology and research enable our trading, market data, and infrastructure systems. Collaborate with fellow quantitative researchers and software engineers to bring your project to success. Learn from the best, using technology built for speed and precision. What we're looking for Currently in your (pen)ultimate year studying a quantitative field at a top university in Singapore Available full-time in Singapore for a duration of 12 weeks over the summer of 2027, starting on the 10th of May Working knowledge of Python Comfort with probability, statistics, and working with messy real-world data A critic

About BlockTech BlockTech is a fast-paced algorithmic market maker at the frontier of cryptocurrency derivatives and spot markets, expanding into new markets. We employ algorithms to trade our own capital, 24/7, across some of the most data-rich venues in finance. For the Summer of 2027, we're looking for a Quantitative Research Intern to join our option pricing team in Amsterdam. The role This is an 8-10 week summer internship at our Amsterdam office, giving you a unique opportunity to work on an end-to-end project with a real and direct business impact. You’ll work in a small team and get the chance to understand how a trading firm actually works from the inside. You will: Participate in a customized training program that will give you an understanding of financial markets in general, the company and the project. Own a research project from design to deployment guided by experienced Quantitative Researchers. Understand how technology and research enable our trading, market data, and infrastructure systems Collaborate with fellow researchers and software engineers to bring your project to success Learn from the best, all while leveraging cutting-edge technology What we're looking for Currently in your (pen)ultimate year and enrolled in, or planning to pursue, at least a Master’s degree in a quantitative field at a top European university. Available full-time in Amsterdam, for a duration of 8 - 10 weeks over the summer of 2027, starting on the 5th of July Working knowledge of Python A critical mind that follows things until completion, high ownership, and clear communication in English What's in it for you? A summer internship in a relaxed and modern office in Amsterdam A dedicated mentor, a team of fellow interns and full-time quantitative researchers, an in-house training program, and exposure to how engineering, research, and trading actually work together The opportunity to work at the forefront of automated trading, in an environment that embraces AI to both ac

About Cubist: Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. About the team: The team is focused on systematic equity trading. It is established, yet still pre-trade, offering an exciting opportunity to join at an early stage and be involved in a broad range of development areas. The team members come from a mixture of quant analyst and development backgrounds, using the combination of skills to achieve a common goal. All team members are based in the London office five days a week to maximize communication and interaction. Role and Responsibilities: An ideal growth role to suit a developer looking for additional responsibilities and independence. Responsibilities may include: • Building components for all aspects of live trading and research environments. • Driving automation and robustness of our processes. • Developing robust data checking and handling procedures. • Monitoring and troubleshooting any issues that should arise. • Shared responsibility for timely and correct operation of trading systems. Requirements: • Bachelor’s degree or equivalent in computer science or other STEM discipline • 2+ years commercial experience with Python and its data science libraries on Linux. • Pragmatic balance between attention to detail and delivery focus. • Ability to work with ambiguous requirements. • Self-driven, owning problems while knowing when to seek advice. • Knowledge of finance and trading systems a plus. • Experience with a systems programming language (

About Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. Role: A new Cubist portfolio management team specializing in the systematic trading of equities is looking for a Quant Researcher whose core focus will be working on mid-frequency alpha strategies. Joining the team will provide a unique opportunity to be involved with the early stages of a product launch and develop within a growing team. Responsibilities: Perform rigorous and innovative research to discover systematic anomalies in the equities market End-to-end development, including alpha idea generation, data processing, strategy backtesting, optimization, and production implementation Identify and evaluate new datasets for stock return prediction Maintain and improve portfolio trading in a production environment Contribute to the analysis framework for scalable research Requirements: MS or PhD in a quantitative discipline 0-2 years of professional work experience A background in financial markets is not necessary, but an interest in the field is essential Proven expertise in Python and handling large datasets Fluency in data science practices, e.g., feature engineering. Experience with machine learning is a plus Highly motivated, curious, and critical thinker Collaborative mindset with strong independent research abilities Commitment to the highest ethical standards

JOB RESPONSIBILITIES: A highly collaborative, fast-growing team at Internal Alpha Capture (IAC), Point72 is developing AI-driven equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, proprietary data sources, and unparalleled computing power. We are looking for exceptional machine learning researchers to join our efforts. Researchers will work closely with our experienced team members and apply the full breadth of their machine learning knowledge to unique, proprietary datasets, and develop novel trading signals that have high impact. Prior experience in the financial industry is not required. Key responsibilities may include: Managing all aspects of the research process, including ideation, method selection, implementation, evaluation, and eventual application. Identifying, adapting, and extending existing models in the broad field of machine learning; conducting novel research as needed, to develop new signals that can enhance portfolio returns, or predict other variables of interests. Staying up to date on the advances in AI/ML and related technological innovations to provide recommendations on new models and tools and identify emerging opportunities. DESIRABLE CANDIDATES: Master’s or PhD in machine learning, computer science, statistics, or related fields. Knowledge and experience in any of the following areas are strongly preferred: modern sequence models, graph neutral nets, reinforcement learning, LLMs. Prior research experience utilizing machine learning over large, possibly noisy, data sets. Strong analytical and quantitative skills, and a detail-oriented mindset. Strong proficiency in machine learning libraries such as Torch, JAX or TensorFlow. Competence in Python, cluster environment, and general software engineering principles (source control, testing, collaborative workflow). Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly coll