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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