Quantitative Software Engineer
Summary
Quantitative developer at a proprietary trading firm in Chicago, owning the path from research to live trading: building backtesting/simulation infrastructure, feature and signal pipelines, and optimizing strategies. Core stack is production Python (pandas/polars) with ML applied to systematic trading; low-latency experience is a plus.
Our client, a leading proprietary trading firm, is hiring a Quantitative Developer to take ownership of the entire journey from research to live production. The role sits between research and engineering, with fast feedback loops from first idea to live trading. You’ll build the systems that turn quantitative ideas into measurable edge, and see directly how your work drives results.
What You’ll Do:
- Build and maintain systems bridging research and production, enabling fast iteration from concept to deployment
- Develop realistic simulation and backtesting infrastructure that captures latency, market microstructure and real-world constraints
- Define, calculate and manage features across instruments, market regimes and time horizons
- Own feature and signal pipelines, keeping delivery clean and consistent from research through to execution
- Help optimize strategies, weighing expected performance against practical constraints
- Troubleshoot issues end-to-end across research and execution
What You’ll Bring:
- 3–7 years in quantitative software development, ideally at a trading firm or systematic fund
- Strong production Python, including data analysis tools (pandas, polars or similar)
- Solid foundation in probability, statistics and time series analysis; familiarity with back-testing and simulation frameworks
- Good understanding of ML as applied to systematic strategies, from research to production
- Low-latency systems experience is a plus
- Comfortable working across both research and engineering teams