Quantitative Software Engineer

Fintal Partners; Chicago (IL); Presencial; USD 140.000 - 210.000; Jornada completa

Descripción de la vacante

Fintal Partners in Chicago seeks a Quantitative Developer to own the end-to-end lifecycle from research ideas to live trading. You will build rapid feedback loops between research and production, enabling fast iteration and measurable edge.

You will design and maintain backtesting and simulation infra, manage feature pipelines, and collaborate with research and engineering teams to optimize strategies while addressing real-world constraints.

Formación

• 3–7 years of quantitative software development experience, ideally in a trading firm or systematic fund.
• Strong production Python skills with data analysis experience (Pandas/Polars).
• Solid foundation in probability, statistics and time series analysis; familiarity with back-testing and simulation frameworks.

Responsabilidades

• Build and maintain systems bridging research and production to enable 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 end-to-end issues across research and execution.

Conocimientos

Production Python

Time Series Analysis

Probability & Statistics

ML for Trading

Feature Engineering

Herramientas

Pandas

Polars

Descripción del empleo

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