Quantitative Software Developer

Cubist Systematic Strategies, an affiliate of Point
72, 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.

• 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

• 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, tensor flow, 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