Quantitative Developer

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

Job summary

Fintal Partners seeks a Quantitative Developer to own the journey from research to live production within a fast-paced trading environment. You will build systems bridging research and engineering, delivering measurable edge with rapid feedback from idea to execution.

Responsibilities include designing backtesting infrastructure, implementing low-latency data pipelines, and collaborating with research and trading teams to turn models into deployable strategies.

Qualifications

• 3–7 years in quantitative software development.
• Proficient Python with data analysis libraries.
• Strong foundation in probability, statistics and time series.
• Familiarity with back-testing and simulation frameworks.
• ML knowledge for systematic strategies is a plus.

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 trading

Cross-team collaboration

Tools

Pandas/Polars

Backtesting 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