Quantitative Python Engineer — Research to Production Edge

IMC Trading; Illinois; On-site; USD 200,000 - 225,000; Full time

Job summary

IMC Trading in Illinois is seeking a Quantitative Developer to own the full path from research to production. You will build systems that turn quantitative insights into measurable edge, with direct visibility into how your work creates impact.

Your core responsibilities include designing high-fidelity simulation and backtesting infrastructure, defining and curating features across instruments and regimes, and owning pipelines from research to execution.

Qualifications

• 3-7 years of experience in quantitative software development, preferably at a trading firm or systematic fund.
• Strong production experience in Python, including data analysis workflows (pandas, polars, or similar).
• Solid grounding in probability, statistics, and time series analysis; familiarity with backtesting and simulation frameworks.
• Solid understanding of ML concepts as applied to systematic strategies, from research through production.
• Experience with low-latency systems is valuable.
• Ability to work fluidly across research and engineering teams.

Responsibilities

• Build and maintain systems that span research and production for rapid iteration.
• Design high-fidelity simulation and backtesting infrastructure modeling latency and microstructure.
• Define, compute, and curate features across instruments, regimes, and time horizons.
• Own feature and signal pipelines from research to execution.
• Contribute to strategy optimization balancing performance with real-world constraints.
• Debug issues end-to-end across research and execution.

Skills

Python

Data analysis

Time series analysis

Probability & statistics

Low-latency systems

Cross-functional collaboration

Tools

Pandas

Polars

Backtesting frameworks

Job description

IMC Trading in Illinois is seeking a Quantitative Developer to own the full path from research to production. You will build systems that turn quantitative insights into measurable edge, with direct visibility into how your work creates impact.

Your core responsibilities include designing high-fidelity simulation and backtesting infrastructure, defining and curating features across instruments and regimes, and owning pipelines from research to execution.