Systematic Trader Jobs

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 Lead a specialized global network team that owns the critical path between trading strategies and markets across collocated sites and inter-site connectivity Own the architectural roadmap for the collocated trading environment and wide area network (WAN) connecting exchange sites, proximity data centers, venues, brokers, and data providers Design and operate ultra-low-latency network fabrics, including layer 1 topologies, optical transport, structured cabling, patching strategy, and capacity planning Evaluate, procure, validate, and monitor inter-site circuits to ensure route latency, stability, resilience, and performance meet production trading requirements Manage BGP, IP routing, load balancing, firewall, and segmentation architecture across the WAN and extranet connectivity protecting the trading estate Own end-to-end market data connectivity, including multicast and unicast feed delivery, gap and loss analysis, arbitration paths, and line-rate

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

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: Cubist is looking for a support engineer/quantitative developer who will work on a growing L2/L3 support team for quantitative trading systems, high‑frequency trading infrastructure, real time analytics, and research infrastructure. This role will require close collaboration with multiple teams at Cubist, including multiple Portfolio Manager (PM) teams, Central Research Technology, and Execution Services. The role offers career growth through the opportunity to work on the development of the underlying systems. Role/Responsibilities: Troubleshooting/resolution of quantitative trading systems and other live analytics processes System monitoring, including development of better processes and tools New feature development in Python/C++ Configuration and change management Onboarding assistance Requirements: 2+ years of professional support and/or software engineering experience Experience with trading systems support (co-located low-latency systems a strong plus) Fluency with C++, Python and SQL Familiarity with software delivery lifecycle and production deployment Cloud experience is a strong plus Team player and strong communicator

About Cubist Cubist Systematic Strategies, an affiliate of Point72, 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. Job Description The Central Research Technology team, which builds strategic solutions for research and live trading of quantitative strategies across multiple frequencies and products, is seeking a highly talented intern to work with the team in January. This is a unique opportunity to help design and build the next generation of research and quant trading systems for Cubist. Desirable Candidates Undergraduate or graduate candidates in computer science or engineering Significant experience in Python and/or C++ Interest in open source research tools for data science and machine learning Basic knowledge of linux, git, conda, and CI processes Knowledge of cloud, databases and distributed or streaming compute is a plus Reasonable quantitative and statistical skills Experience with Finance preferred Clear, concise, and proactive communicator Detail oriented and quick learner in a fast-paced environment Team player with strong pride of ownership 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. 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: 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

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

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. JOB DESCRIPTION Researchers are responsible for independently conducting quantitative finance research with a focus on statistical and predictive models. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX Strong analytical and quantitative skills Demonstrated ability to conduct independent research utilizing large data sets Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that yo

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. JOB DESCRIPTION Researchers are responsible for independently conducting quantitative finance research with a focus on statistical and predictive models. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring. Some successful researchers have joined us from similar backgrounds at other firms. Others have joined from related fields or directly from academia and have thrived with hands on guidance from our large team of experienced portfolio managers and researchers. Our most exceptional team members combine strong technical skills and a passion for problem solving with an intense curiosity about financial markets and human behavior. DESIRABLE CANDIDATES MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX Strong analytical and quantitative skills Demonstrated ability to conduct independent research utilizing large data sets Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl Detail-oriented Willing to take ownership of his/her work, working both independently and within a small team We’re looking for exceptional colleagues with unparalleled passion. If you’d like your resume to stand out, tell us about your exceptional personal achievements, even if they have nothing to do with finance. Of course we love to hear more about specific engineering or data projects that yo

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 Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative research with a focus on predictive models. You will be trained in all aspects of systematic trading from idea generation all the way to practical trading considerations. Successful hires will ultimately become thought leaders within our collaborative research group. RESPONSIBILITIES Conduct original quantitative alpha signal research Follow, digest and analyze the latest academic research Manage all aspects of the research process, including idea generation, data analysis, hypothesis development and testing, alpha discovery, trading strategy generation, backtesting and portfolio analysis Build analytical tools to supplement our shared research framework REQUIRMENTS B.S., M.S. or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline. Programming in Python (or comparable language) and working knowledge of SQL Strong analytical and quantitative skills. Willingness to take ownership of his/her work. Ability to work both independently and collaboratively within a team. Strong desire to deliver high quality results in a timely fashion. Detail-oriented. Prior experience in the financial services industry is not required. A 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 Entry-Level Quantitative Researchers are responsible for conducting rigorous quantitative research with a focus on predictive models. You will be trained in all aspects of systematic trading from idea generation all the way to practical trading considerations. Successful hires will ultimately become thought leaders within our collaborative research group. RESPONSIBILITIES Conduct original quantitative alpha signal research Follow, digest and analyze the latest academic research Manage all aspects of the research process, including idea generation, data analysis, hypothesis development and testing, alpha discovery, trading strategy generation, backtesting and portfolio analysis Build analytical tools to supplement our shared research framework REQUIRMENTS B.S., M.S. or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline. Programming in Python (or comparable language) and working knowledge of SQL Strong analytical and quantitative skills. Willingness to take ownership of his/her work. Ability to work both independently and collaboratively within a team. Strong desire to deliver high quality results in a timely fashion. Detail-oriented. Prior experience in the financial services industry is not required. A commitment to the highest ethical standards.

A Career with 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 We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modeling in finance. You will join a team that plays a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe. Specifically, you will: Serve as a frontline owner for thousands of mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with portfolio managers, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s Required Bachelor’s degree with a focus in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments; familiarity with Databricks is a plus. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal

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-

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 The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance. RESPONSIBILITIES Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas. Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization. Maintaining and improving portfolio trading in production environments. REQUIREMENTS Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline. 2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus. Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning. Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas. Ability to work both independently and collaboratively within a team. Commitment to the highest ethical standards.