Quantitative Developer - Python

Fintal Partners; Chicago (IL); On-site; USD 140,000 - 210,000; Full time

Job summary

Fintal Partners in Chicago is seeking a Quantitative Developer to build production-grade Python tooling and data pipelines for large-scale trading datasets. You’ll collaborate with researchers and engineers to translate ideas into robust systems, optimizing performance and memory usage for growing data and workloads.

You should have 3–7 years in quantitative development or related software roles, strong Python skills, and hands-on experience with large datasets, pandas and Polars, and

Qualifications

• 3–7 years of experience in quantitative development or related software roles.
• Excellent Python coding skills with production systems experience.
• Hands-on experience handling large datasets, data pipelines, and performance optimization.
• Familiarity with quantitative research, backtesting, and simulation workflows.
• Understanding of time series analysis and machine learning concepts for systematic trading.

Responsibilities

• Develop and optimize Python systems for processing, transforming, and analyzing large-scale financial datasets.
• Build reliable data, feature, and signal pipelines that support quantitative research and live trading.
• Improve the speed, scalability, and memory efficiency of research workflows.
• Develop backtesting and simulation tools that account for market behavior and real-world trading constraints.
• Partner with researchers and engineers to translate research ideas into robust production systems.
• Investigate and resolve data quality, performance, and implementation issues across the research-to-production lifecycle.

Skills

Python programming

Large-scale data handling

Pandas

Polars

Time series analysis

ML concepts

Tools

Pandas

Polars

Backtesting

Job description

A leading quantitative trading firm is seeking a Quantitative Developer with strong Python programming skills and experience working with large-scale datasets. This role sits at the intersection of quantitative research and software engineering, building the tools and data pipelines that move trading ideas from research into production.

The primary focus is writing efficient, production-quality Python for demanding data workflows. Experience with both pandas and Polars is highly desirable, alongside the ability to optimize performance as data volumes and computational demands grow.

What you’ll do:

• Develop and optimize Python systems for processing, transforming, and analyzing large-scale financial datasets.
• Build reliable data, feature, and signal pipelines that support quantitative research and live trading.
• Improve the speed, scalability, and memory efficiency of research workflows.
• Develop backtesting and simulation tools that account for market behavior and real-world trading constraints.
• Partner with researchers and engineers to translate research ideas into robust production systems.
• Investigate and resolve data quality, performance, and implementation issues across the research-to-production lifecycle.

Qualifications:

• 3–7 years of experience in quantitative development or a closely related software engineering role, ideally within a trading firm or systematic investment fund.
• Excellent Python coding skills, with a track record of building and maintaining production systems.
• Strong proficiency in pandas and/or Polars, ideally with practical experience in both.
• Familiarity with quantitative research, backtesting, and simulation workflows.
• Hands-on experience handling large datasets, including efficient data manipulation, pipeline development, and performance optimization.
• A strong foundation in probability, statistics, and time series analysis.
• An understanding of machine learning concepts and their application to systematic trading.
• The ability to collaborate effectively across research and engineering teams.

Experience with low-latency trading systems is a plus.