Quantitative Developer

Our Client is a systematic hedge fund that turns thousands of statistical algorithms and machine-learning models into market-neutral portfolios across equities, futures and other liquid markets. As a Quantitative Developer you will convert researcher prototypes into reliable, high-performance production systems so that every new signal can be tested, combined and traded at scale. Your code will sit on the critical path between idea and P&L.

Performance Objectives

• Productionize new alpha and strategy models from research hand-off to live trading within two weeks, with full unit, simulation and paper-trading coverage.
• Reduce end-to-end latency of the research-to-execution pipeline by 30% within the first six months through profiling, vectorization and smarter data layouts.
• Own the daily build, back-test and live-risk run of at least one major strategy family, keeping simulation-to-live slippage inside agreed bounds.
• Deliver reusable Python/C++ libraries and data APIs that let researchers iterate 2× faster without sacrificing numerical accuracy or reproducibility.
• Implement automated monitoring, alerting and rollback so that any production incident is diagnosed and contained in under 15 minutes.
• Onboard at least two new data sources or asset classes per quarter, including normalization, quality gates and integration into the simulation engine.

Environment & Resources

You will sit with a small, highly accomplished team of researchers, data engineers and trading-systems specialists in Stamford (NYC office opening 2026). You report to the Head of Trading Technology, work on Linux with Python, C++, SQL, Parquet/Arrow and our internal simulation cluster, and have direct access to production market data, compute budget and senior researchers. The environment is collaborative, casual and high-ownership.

Essential Qualifications

• BS/MS in Computer Science, Mathematics, Physics or related STEM field.
• Proven ability to take numerical research code (Python/NumPy/Pandas) into robust, tested production services (C++ or highly optimized Python).
• Strong Linux, scripting and SQL skills; experience with large financial or scientific datasets.
• Demonstrated track record of measuring, profiling and improving performance of compute- or I/O-bound systems.
• Comfort working independently in a fast-paced, research-driven setting while communicating clearly with non-engineers.

Role Selling Points

• Direct impact: your implementations go live and generate real P&L, not just internal reports.
• Fully paid PPO health, dental and vision for you and dependents, plus performance bonus.
• Weekly company meals, pre-tax commuter benefits and a genuinely friendly, low-ego culture.
• Work on the hardest problems in systematic trading with researchers who publish and practitioners who trade.

If you want to ship the next generation of machine-learning strategies into production, apply now.