Mid Level Quant Developer Jobs
Mid level quant developer jobs go to developers ready to own models end to end, guide junior team members, and make quantitative decisions with limited oversight. Hiring runs across Investment & Asset Management, Banking & Financial Services, and Staffing & Recruiting, with 7% of roles offered remotely or hybrid, and employers like Saragossa, Millennium, and Trexquant Investment LP competing for developers at this level now.
Find JobsOverview
Showing 5 of 15+ Mid Level Quant Developer jobs
INTRODUCTION
Quantitative Developers work closely with Quantitative Researchers, Portfolio Management and other teams to develop, evolve, and maintain core components and systems within the quantitative research and production life cycles. They develop components such as optimizers; tools and computing frameworks like simulation and backtesting platforms; and systems including market data ingestion, trading execution, and order management. They are responsible for the end-to-end implementation and support of model execution, portfolio construction and management based on mathematical and computer science methodologies.
Responsibilities
- Develop quantitative research platforms and tools, such as simulation and backtesting systems, to support quantitative research computations in both interactive and batch-processing modes.
- Participate in algorithm research and implementation optimization for workflows like portfolio optimization, based on a deep understanding of business logic and engineering expertise.
- Build, optimize, and maintain low-latency trading pipelines and order execution systems, particularly within the context of global markets.
- Utilize or develop high-performance and parallel computing frameworks or libraries to optimize the performance of trading components in both research and production environments.
- Contribute to emerging business areas, including new investment horizons, trading frequencies, asset classes, and global markets.
QUALIFICATIONS
- Bachelor’s degree or above, majoring in Computer Science, Software Engineering, Mathematics, or related STEM fields.
- Solid foundation in algorithms, data structures, and proficiency in software development within Linux environments.
- 3+ years of experience in quantitative software engineering, with proven experience in designing and developing research and production quantitative systems. Strong project management skills.
- Hands-on professional experience with modern C++ or Python, including concurrent and parallel programming.
PREFERRED QUALIFICATIONS
- Experience in U.S. futures and equities markets and relevant quantitative trading systems.
- Deep understanding of low-latency, production trading software systems.
- Experience with quantitative research systems, linear algebra, numerical computations, and numerical optimization.
- Experience applying high-performance computing techniques to process large-scale time-series financial datasets.
- Experience with GPU computing and distributed computing.
- Solid understanding of computer science fundamentals such as architecture, OS and compilers.
- Experience with machine learning frameworks such as PyTorch.
INTRODUCTION
Quantitative Developers work closely with Quantitative Researchers, Portfolio Management and other teams to develop, evolve, and maintain core components and systems within the quantitative research and production life cycles. They develop components such as optimizers; tools and computing frameworks like simulation and backtesting platforms; and systems including market data ingestion, trading execution, and order management. They are responsible for the end-to-end implementation and support of model execution, portfolio construction and management based on mathematical and computer science methodologies.
Responsibilities
- Develop quantitative research platforms and tools, such as simulation and backtesting systems, to support quantitative research computations in both interactive and batch-processing modes.
- Participate in algorithm research and implementation optimization for workflows like portfolio optimization, based on a deep understanding of business logic and engineering expertise.
- Build, optimize, and maintain low-latency trading pipelines and order execution systems, particularly within the context of global markets.
- Utilize or develop high-performance and parallel computing frameworks or libraries to optimize the performance of trading components in both research and production environments.
- Contribute to emerging business areas, including new investment horizons, trading frequencies, asset classes, and global markets.
QUALIFICATIONS
- Bachelor’s degree or above, majoring in Computer Science, Software Engineering, Mathematics, or related STEM fields.
- Solid foundation in algorithms, data structures, and proficiency in software development within Linux environments.
- 3+ years of experience in quantitative software engineering, with proven experience in designing and developing research and production quantitative systems. Strong project management skills.
- Hands-on professional experience with modern C++ or Python, including concurrent and parallel programming.
PREFERRED QUALIFICATIONS
- Experience in U.S. futures and equities markets and relevant quantitative trading systems.
- Deep understanding of low-latency, production trading software systems.
- Experience with quantitative research systems, linear algebra, numerical computations, and numerical optimization.
- Experience applying high-performance computing techniques to process large-scale time-series financial datasets.
- Experience with GPU computing and distributed computing.
- Solid understanding of computer science fundamentals such as architecture, OS and compilers.
- Experience with machine learning frameworks such as PyTorch.
See All 15 Mid Level Quant Developer Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsMid Level Quant Developer Job Market
Who's Hiring
Top Industries Hiring
- Investment & Asset Management
- Banking & Financial Services
- Staffing & Recruiting
- Technology & Software
- Government & Public Sector
Mid Level Quant Developer Jobs: Frequently Asked Questions
How do I get a mid level quant developer job?
Position yourself around ownership, not just contribution. Highlight projects where you drove the quantitative design, debugged production models, or improved a strategy's performance without heavy supervision. Mid level hiring managers want to see that you can operate independently, so frame your resume around decisions you made and outcomes you delivered, not tasks you completed under direction.
Which companies hire mid level quant developers?
Companies hiring mid level quant developers right now include Saragossa, Millennium, and Trexquant Investment LP, based on current listings on Migrate Mate as of November 2026. At this level, hiring comes from a mix of established financial institutions, proprietary trading firms, and technology companies that run internal quantitative research teams.
Are there remote mid level quant developer jobs?
Yes, though availability varies by employer and role type. About 7% of mid level quant developer openings are remote or hybrid as of November 2026, with hybrid arrangements more common at firms where collaboration on live trading systems or research infrastructure is part of the role.
How do I move up to a mid level quant developer role?
Moving from entry level to mid level means building depth in a specific area, such as derivatives pricing, risk modeling, or execution algorithms, while taking on progressively larger scope. Employers look for evidence that you have owned a project from design through deployment, mentored peers, and demonstrated measurable impact on a model or system rather than simply implementing others' specifications.
Which industries hire the most mid level quant developers?
Mid Level quant developer roles concentrate in Investment & Asset Management, Banking & Financial Services, and Staffing & Recruiting, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they rely on production-grade quantitative systems that require developers who can maintain, improve, and scale complex models with limited oversight.