Quantitative Developer

Fintal Partners; New York (NY); On-site; USD 140,000 - 230,000; Full time

Job summary

Fintal Partners in New York, NY seeks a Quantitative Developer to join the research and trading teams. You will work at the intersection of software engineering, quantitative research, and live trading to build tools, infrastructure, and production systems powering research and strategies.

The role emphasizes collaboration with researchers and traders to deploy models, improve performance, and scale data pipelines.

Qualifications

• 3+ years of professional software development experience.
• Experience with scientific computing libraries such as NumPy, Pandas, Polars, or similar.
• Experience building scalable software, data pipelines, or distributed systems.
• Strong understanding of algorithms, data structures, and software engineering best practices.
• Excellent problem-solving skills and the ability to thrive in a fast-paced, collaborative environment.
• Familiarity with market data, backtesting frameworks, or quantitative research infrastructure.

Responsibilities

• Build and enhance the software infrastructure used by quantitative researchers and traders
• Design and develop scalable Python applications supporting research and live trading
• Develop tools, libraries, and frameworks that accelerate quantitative research workflows
• Partner closely with researchers to deploy models and strategies into production
• Improve the performance, reliability, and scalability of research and trading platforms
• Build and maintain data pipelines, APIs, and distributed systems for market data and analytics
• Participate in architecture discussions, code reviews, and technical design decisions

Skills

NumPy

Pandas

Polars

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a related technical field

Tools

C++

Linux

Bash

Job description

We're partnering with a leading quantitative trading firm that's looking to add a Quantitative Developer to one of its research and trading teams.

This is an opportunity to work at the intersection of software engineering, quantitative research, and live trading. You'll collaborate closely with researchers and traders to build the tools, infrastructure, and production systems that power the firm's research platform and trading strategies. Your work will have a direct impact on research productivity, strategy development, and trading performance.

If you enjoy solving complex technical problems, building scalable systems, and working in a highly collaborative engineering environment, this is an exceptional opportunity.

Responsibilities

• Build and enhance the software infrastructure used by quantitative researchers and traders
• Design and develop scalable Python applications supporting research and live trading
• Develop tools, libraries, and frameworks that accelerate quantitative research workflows
• Partner closely with researchers to deploy models and strategies into production
• Improve the performance, reliability, and scalability of research and trading platforms
• Build and maintain data pipelines, APIs, and distributed systems for market data and analytics
• Participate in architecture discussions, code reviews, and technical design decisions

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Physics, or a related technical field
• 3+ years of professional software development experience
• Experience working with scientific computing libraries such as NumPy, Pandas, Polars, or similar
• Experience building scalable software, data pipelines, or distributed systems
• Strong understanding of algorithms, data structures, and software engineering best practices
• Excellent problem-solving skills and the ability to thrive in a fast-paced, collaborative environment

Preferred Qualifications

• Experience working at a proprietary trading firm, hedge fund, market maker, or quantitative investment firm
• Experience supporting quantitative researchers or systematic trading teams
• Experience with C++, Linux, Bash, or other systems programming tools
• Familiarity with market data, backtesting frameworks, or quantitative research infrastructure