Quantitative Developer

Fintal Partners; Chicago (IL); On-site; USD 180,000 - 240,000; Full time

Job summary

Fintal Partners is seeking a Quantitative Developer to own the journey from research to live trading. The role sits between research and engineering, enabling fast feedback loops from idea to execution and directly impacting trading results.

You’ll build systems that bridge research and production, develop backtesting and simulation infrastructure, and define feature pipelines across instruments and time horizons. Collaboration across research and engineering is essential to success.

Qualifications

• 3–7 years of quantitative software development experience.
• Strong Python production skills and data analysis using Pandas/Polars.
• Background in probability, statistics and time series analysis.

Responsibilities

• Build and maintain systems bridging research and production for fast iteration.
• Develop realistic simulation and backtesting infrastructure.
• Define and manage features across instruments, regimes and horizons.
• Own feature and signal pipelines from research to execution.
• Help optimize strategies considering practical constraints.
• Troubleshoot end-to-end across research and execution.

Skills

Python

Data analysis tools

Time series analysis

ML for trading

Low-latency systems

Cross-team collaboration

Tools

Pandas

Polars

Back-testing frameworks

Job description

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