Point72
Quantitative Developer
Point72, New York, New York, us, 10261
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 simulationRefining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting componentsBuilding tools for signal blending, simulation, portfolio construction, the research framework, and dashboardsMaintaining and updating the platform, ensuring its stability, robustness, and securityDeveloping robust data checking and storage proceduresTroubleshooting and resolving any systems related issues and handle the release of code fixes and enhancementsREQUIREMENTS
Bachelor's degree or higher in computer science or other STEM disciplineAdvanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internalsExperience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax)Proficiency with LinuxHands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control)Knowledge of one or more of: distributed systems, databases, ML engineering, AWSStrong quantitative and analytical skills; command of linear algebra, statistics, and machine learning would be helpfulProficiency with C/C++ is a plusKnowledge of financial markets is a plusCommitment to the highest ethical standards
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 simulationRefining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting componentsBuilding tools for signal blending, simulation, portfolio construction, the research framework, and dashboardsMaintaining and updating the platform, ensuring its stability, robustness, and securityDeveloping robust data checking and storage proceduresTroubleshooting and resolving any systems related issues and handle the release of code fixes and enhancementsREQUIREMENTS
Bachelor's degree or higher in computer science or other STEM disciplineAdvanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internalsExperience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax)Proficiency with LinuxHands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control)Knowledge of one or more of: distributed systems, databases, ML engineering, AWSStrong quantitative and analytical skills; command of linear algebra, statistics, and machine learning would be helpfulProficiency with C/C++ is a plusKnowledge of financial markets is a plusCommitment to the highest ethical standards