Quantitative Software Engineer

Fintal Partners; Chicago (IL); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

None

Job summary

Fintal Partners is seeking a Quantitative Developer to own the journey from research to live production. You will build systems bridging research and engineering to turn ideas into measurable trading edge, with fast feedback loops from concept to deployment.

You will design and maintain simulation/backtesting infra, manage features across instruments and regimes, and work across research and engineering to optimize strategies and troubleshoot end-to-end.

Qualifications

• 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.

Responsibilities

• 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

Skills

Python

Time series analysis

Probability & statistics

ML for systematic strategies

Research to production

Tools

Pandas

Polars

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