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:
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Building components for both live trading and simulation
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Refining and increasing automation and robustness of the research infrastructure including alpha estimation, risk modeling, and backtesting components
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Building tools for signal blending, simulation, portfolio construction, the research framework, and dashboards
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Maintaining and updating the platform, ensuring its stability, robustness, and security
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Developing robust data checking and storage procedures
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Troubleshooting and resolving any systems related issues and handle the release of code fixes and enhancements
REQUIREMENTS:
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Bachelor’s degree or higher in computer science or other STEM discipline
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Advanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn), with an understanding of Python and library internals
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Experience contributing to core Python numerical libraries is a huge plus (numpy, tensorflow, torch, jax)
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Proficiency with Linux
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Hands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control)
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Strong quantitative and analytical skills; command of linear algebra, statistics, and machine learning would be helpful
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Proficiency with C/C++ is a plus
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Experience with designing and implementing trading systems is a plus