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Point72 Asset Management, L.P

Quantitative Developer

Point72 Asset Management, L.P, New York, New York, us, 10261

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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

The annual base salary range for this role is $200,000-$300,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

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