Quantitative Python Engineer: From Research to Live Trading

IMC; Chicago (IL); Hybrid; USD 150,000 - 210,000; Full time

Job summary

IMC B.V. is seeking a Quantitative Developer to own the full path from research to production in Chicago. You will build systems turning quantitative insights into measurable edge, with visibility into impact on live trading.

The role blends research and engineering with tight feedback loops, enabling rapid iteration from idea to production and offering exposure to latency-sensitive, real-time strategies.

Qualifications

• 3-7 years 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.
• Strong 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, enabling rapid iteration from idea to production.
• Design high-fidelity simulation and backtesting infrastructure that models latency, microstructure, and real-world constraints.
• Define, compute, and curate features across instruments, regimes, and time horizons.
• Own feature and signal pipelines, ensuring clean, consistent delivery from research to execution.
• Contribute to strategy optimization, balancing expected performance with real-world constraints.
• Debug issues end-to-end across research and execution.

Skills

Python

Data analysis

Time series analysis

Probability / statistics

ML for trading

Low-latency systems

Cross-team collaboration

Tools

Pandas

Polars

Backtesting frameworks

Job description

IMC B.V. is seeking a Quantitative Developer to own the full path from research to production in Chicago. You will build systems turning quantitative insights into measurable edge, with visibility into impact on live trading.

The role blends research and engineering with tight feedback loops, enabling rapid iteration from idea to production and offering exposure to latency-sensitive, real-time strategies.