Cubist Systematic Strategies is looking to enhance its systematic trading strategies and research infrastructure.
Requirements
- 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)
- Proficiency with C/C++ is a plus
- Experience with designing and implementing trading systems is a plus
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
Other
- Bachelor’s degree or higher in computer science or other STEM discipline
- Commitment to the highest ethical standards
