Job description

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.

Requirements

Must-haves

Quantitative Developer
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
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.
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.

Nice-to-haves

Fully paid PPO health, dental and vision for you and dependents, plus performance bonus.

Application prep

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Keywords to mirror

pythonsqlgo

Platform: careers-page
Effort: medium

Benefits

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Dental

Vision