Quantitative Software Developer

Overview In this role you build and refine components for live trading and simulation within Cubist’s research-driven platform. You’ll enhance automation, alpha estimation, risk modeling, backtesting, and tooling for signal blending, portfolio construction, and dashboards. You ensure platform stability, security, and robust data procedures while delivering fixes and enhancements. You’ll collaborate across cross-functional teams to advance scalable, ethical trading infrastructure in a fast-paced financial environment. This is an opportunity to shape core research infrastructure and contribute to high-impact, data-driven trading strategies. ResponsibilitiesBuild components for live trading and simulationAutomate and strengthen research infrastructure (alpha estimation, risk modeling, backtesting)Create tools for signal blending, simulation, portfolio construction, research framework, dashboardsMaintain platform stability, robustness, and securityDevelop robust data validation and storage proceduresTroubleshoot system issues and manage code releases and enhancements Key requirementsBachelor’s degree or higher in computer science or other STEM disciplineAdvanced proficiency in Python and its ecosystem (numpy, pandas, polars, scikit-learn)Experience with LinuxHands-on experience with software architecture and engineering best practices (testing, CI/CD, monitoring, profiling, version control)Strong quantitative and analytical skills; knowledge of linear algebra, statistics, and machine learning helpfulProficiency with C/C++ is a plusExperience with designing and implementing trading systems is a plusCommitment to the highest ethical standardsstrong analytical thinkingproblem-solving mindsetteam collaborationPython (numpy, pandas, polars, scikit-learn)numerical libraries (numpy, tensorflow, torch, jax)Linux proficiency