Point72 Fund Flow Analyst Jobs

System Engineer, Linux 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 Support, maintain, and troubleshoot Linux systems in production and development environments Assist with system provisioning, configuration, and lifecycle management Monitor system performance, availability, and capacity; respond to incidents and outages Work closely with developers and quants to support research and trading workloads Automate operational tasks using scripting and configuration management tools Assist with patching, upgrades, and vulnerability remediation Maintain documentation and operational runbooks Participate in on-call rotation (as appropriate for level) What’s REQUIRED Bachelor’s degree in computer science, information technology, engineering, or a related field. 5+ years of professional experience administering Ubuntu Linux systems and ZFS Strong understanding of Linux fundamentals including processes, memory, CPU, filesystems, and networking as well as systemd, cron, logging, and package manag

A Career with Point72’s Market Intelligence Team On our proprietary research team—Market Intelligence—you’ll partner with our Investment Professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques to alternative data sets. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our industry researchers, product managers, and data scientists and engineers work together to build compliant research products. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. What you'll do Data Engineers on the Proprietary Research team design and build solutions that enable investment professionals to effortlessly, extract insights from large, complex compliance approved structured and unstructured data sets. As a member of our Data Engineering team, you will work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end data pipelines and tools that that help extract the most value out of Point72’s data assets. In this role, you will: Develop and support big data processing pipelines including but not limited to ingestion, transformation, and end-customer delivery Build out cloud-based infrastructure using distributed techniques for other data engineers / data scientists / researchers Be at the forefront of new technology developments with respect to the handling and processing of big data and conduct proof of concepts evaluations of new technologies Build and support visualization and exploration capabilities around our big data sets. What's required Experience or demonstrated interest in big data technologies 3+ years of experience in Data Engineering or related field Strong experience in Python Development Experience with Spark or Scala Ability to

A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Design and build scalable, high-performance backend systems that power investment services and AI-driven applications, and own their end-to-end lifecycle Build and operate robust data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers Integrate and productionize generative AI capabilities and large language model solutions, including model serving, embeddings, and API-based workflows to augment investment workflows Implement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security Optimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response Lead cross-functional delivery of prototypes into production by collaborating with data scientists, researchers, product owners, and operations teams Build and maintain CI/CD pipelines, automated testing, and deployment practices to accelerate safe delivery and rollback of services Mentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap Collaborate with security, compliance, and infrastructure partners to ensure data governance, access controls, and operational controls are integrated into solutions WHAT'S REQUIRED Bachelor's degree in computer science, software engineering, or a related technical field At least 5 years of professional software enginee

ABOUT CANVAS On our proprietary research team—Market Intelligence—you’ll partner with our investment professionals and Compliance team to uncover insights about companies, industries, and the broader economy through deep fundamental research. Canvas is the supply chain research group within Market Intelligence. Canvas conducts compliant supply chain research by developing deep industry expertise, talking with private company executives, and synthesizing information for portfolio managers and analysts—our team produces impactful research that will change the way you look at the world. ROLE SUMMARY When you join the Canvas team, you’re signing up for the learning experience of your life. You will never look at anything the same—from grocery stores to tires to semiconductors. Every day you will speak with some of the most successful private company executives and learn about the businesses they’ve spent their lives building. You will synthesize your findings in comprehensive reports that are consumed by our investment professionals. Other Market Intelligence divisions perform quantitative research to explain what is going on in an industry. As a fundamental researcher, your qualitative research will explain why. In this role you will: Become a subject matter expert on an assigned industry Learn from small, medium, and large private company executives about their businesses and the industries in which they operate, including gathering qualitative data on what is happening (e.g., structural shifts, changes in supply/demand dynamics, and emerging competitors, markets, and technologies) and, importantly, why it is happening Synthesize your findings in comprehensive reports that present a view of the industry Gain unparalleled exposure to, and learn from, Compliance approved private company executives across industries, and your colleagues Interact directly with our investment professionals and learn the discretionary investment process WHAT EXCITES YOU Staying current on t

Quant Library Developer, Macro 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 Design, build, and extend core C# analytics services, APIs, and libraries used across the Macro business. Develop and operate high-performance distributed systems with strong guarantees around correctness, latency, and scalability. Build real-time and historical analytics services supporting pricing, risk, and global market data workflows. Design and maintain time-aware (historical and real-time) data models and services, ensuring consistency across analytics use cases. Develop and integrate derived data pipelines and datasets used in research, backtesting, and production analytics. Contribute to API design, data modeling, and system architecture for shared analytics platforms. Integrate analytics services with batch and streaming data pipelines across research and trading workflows. Partner closely with quants and portfolio managers to translate investment requirements into robust platform capabilities. Contribute to

ABOUT PROPRIETARY RESEARCH On our proprietary research team—Market Intelligence— you will uncover insights about companies, industries, and the broader economy through deep compliant fundamental research and applying data science and engineering techniques to alternative data sets. In partnership with our investment professionals and Compliance team, our team of analysts, data scientists and engineers work together to produce compliant research and build tools that inform our firm’s investments. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. WHAT YOU’LL DO As a Sector Analyst for European Equities, you will work with alternative data to gather industry context and business fundamentals. You will then partner with our team of data scientists and engineers to develop analyses that you’ll deliver as synthesized insights to our investment professionals to help aid in their research processes. The work is ever evolving, affording opportunities to tackle new challenges alongside research teammates from diverse backgrounds. Specifically, you will: Analyze and interpret alternative data from multiple sources and develop subject-matter expertise on the key themes and KPIs that drive the industry and companies within your assigned coverage Produce research for internal consumption by our investment professionals across a variety of mediums, including written research reports, verbal communication, and visualization tools Interact directly with our investment professionals to learn the discretionary investment process and help them to drive more informed investment decisions Collaborate with our proprietary research teams including Data Sourcing, Data Science, and Data Engineering, as well as Compliance, to source, evaluate, and draw value from new and existing data assets to produce actionable research for investment professionals WHAT’S REQUIRED

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

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

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.

ROLE/RESPONSIBILTIES: We are seeking a NLP engineer for a NLP research team within Point72. The ideal candidate has a track record of developing modern NLP solutions, including the use of LLMs, agents, RAG, open-source models fine-tuning and deployment, etc. Responsibilities include: Exploring and combining rich internal and external textual datasets Building GenAI solutions, leveraging both internal models and external APIs Formulating research hypothesis to derive alpha Post-training models for specific tasks Benchmarking LLM approaches internal tasks We believe the investment world offers unique opportunities to use modern NLP methods. We are a team ideally situated for that, having access to both internal and commercial datasets, with an end-to-end research philosophy and direct portfolio impact. REQUIREMENTS: Bachelor, Master’s or PhD graduate or candidate in computer science or another quantitative discipline Experience in NLP, particularly LLMs. Proficient in Python, SQL and general software engineering principles (github, testing, etc.) Data science stack familiarity Interest in financial markets Collaborative mindset 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.

Role: The Quant Researcher will report to a Stamford based Portfolio Manager and will focus on: Building, running, and maintaining power dispatch model for ERCOT and other major US ISOs Driving the model’s inputs and architecture to efficiently simulate power grid conditions and marginal pricing Continuously testing and improving the model, ensuring it accurately replicates historical conditions and effectively analyzes forward scenarios Communicating the model’s results and limitations to the wider investment team Responsibilities: Formulate and build a power dispatch model using Python and a commercial solver Collaborate with the PM to optimize model inputs and architecture Ensure the model replicates grid operations from historical conditions Suggest model improvements to decrease forecast error and improve scenario handling Regularly run the model and maintain up-to-date outputs in an internal database Communicate results and limitations to the wider investment team, including publishing results to team dashboards Requirements: Master or PhD in operations research, electrical engineering, applied mathematics, or a related quantitative field 5+ years of direct experience building power dispatch models (SCUC/SCED) using optimization solvers (Gurobi, CPLEX, etc.) Knowledge of power plant dispatch, grid operations (including capacity and AS obligations), and LMP pricing in US power markets Experience using SQL and timeseries databases Proficiency in Python and Git; additional experience with an OOP language a strong plus Domain knowledge in ERCOT, PJM, or CAISO preferred 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 cultu

Role/Responsibilities: We are seeking a quantitative researcher 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 degree 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 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry’s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry’s brightest talent. We’re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit www.Point72.com/working-here.

About Cubist: Cubist Systematic Strategies is one of the world’s premier investment firms. The firm 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 DE 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. Willin

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-

A CAREER WITH POINT72’S MARKET INTELLIGENCE TEAM On our proprietary research team—Market Intelligence—you’ll partner with our investment professionals and Compliance team to work with alternative data to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our sector data analysts, data scientists, data managers, and engineers work together to build compliant research products that are incorporated into the research process of our investment professionals. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. WHAT YOU’LL DO As a sector analyst, you will work with alternative data to gather industry context and business fundamentals. You will then partner with our team of data scientists and engineers to develop analyses that you deliver as synthesized insights to our investment professionals to help aid in their research processes. The work is ever evolving, affording opportunities to tackle new challenges alongside research teammates from diverse backgrounds. Specifically, you will: Analyze and interpret alternative data from multiple sources and develop subject-matter expertise on the key themes and KPIs that drive the industry and companies within your coverage Produce research for internal consumption by our investment professionals across a variety of mediums, including written research reports, verbal communication, and visualization tools Interact directly with our investment professionals to learn the discretionary investment process from them and help drive more informed investment decisions Collaborate with our proprietary research teams including Data Sourcing, Data Science, and Data Engineering, as well as Compliance, to source, explore, and transform