IMC
Quantitative Developer - Python
About this role
IMC seeks a Quantitative Developer to bridge research and production, building systems that transform quantitative strategies into live trading with measurable impact. You'll own the complete lifecycle from idea validation through execution, designing robust backtesting infrastructure and maintaining feature pipelines that power systematic trading.
What you'll do
- Build and maintain research-to-production systems enabling rapid iteration and deployment
- Design high-fidelity simulation and backtesting infrastructure accounting for latency and market microstructure
- Define, compute, and manage features across instruments and time horizons
- Own feature and signal pipelines ensuring consistent data delivery from research to execution
- Optimize trading strategies while balancing performance with real-world constraints
- Debug issues end-to-end across research and execution environments
What they're looking for
- Python production development with data analysis libraries (pandas, polars)
- Probability, statistics, and time series analysis
- Backtesting and simulation framework experience
- Machine learning concepts applied to systematic strategies
- Low-latency systems development
- Cross-functional collaboration between research and engineering teams
- 3-7 years quantitative software development experience
- Trading firm or systematic fund background preferred
Benefits
- Competitive base salary $200,000–$225,000 USD
- Discretionary bonus eligibility
- Paid leave and insurance coverage
- Global trading firm with cutting-edge research environment
- Collaborative, high-performance culture
- Exposure to innovative trading strategies and technologies
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IMC
IMC builds trading technology and financial systems powered by software, machine learning, and hardware engineering. The company is hiring interns and graduate-level engineers and researchers across software, machine learning, and hardware disciplines to develop trading algorithms, research strategies, and collaborative technology solutions.
View all jobs at IMCLikely interview questions
- Walk us through a time you took a quantitative strategy from research to production. What were the biggest challenges in bridging that gap?
- Describe your experience building or working with backtesting and simulation frameworks. How did you handle latency, microstructure, and real-world constraints?