Python Quant Developer Job Description Template

The Python quant developer builds the research and analytics stack that quantitative teams work in day to day. The emphasis is on productive, correct and well tested Python: data access layers, backtesting frameworks, analytics libraries and the tooling that lets researchers move faster without cutting corners. Performance matters, but reliability and clarity matter more, because researchers trust what this code returns.

Typical Duties and Responsibilities

• Build and maintain Python libraries used across research and trading
• Develop data access layers over market, reference and alternative data
• Maintain and extend the backtesting and simulation framework
• Optimize numerical code using vectorisation, Cython or native extensions
• Build analytics and reporting tools for portfolio managers
• Package, version and deploy internal libraries reliably
• Write tests that catch numerical as well as logical regressions
• Support researchers with tooling questions and performance problems
• Maintain documentation for the internal research platform
• Review code and raise the standard of Python across the team

Education

• Bachelor’s degree in computer science, mathematics or a related quantitative field

Required Skills and Experience

• 3+ years of professional Python development, ideally in finance
• Deep knowledge of NumPy, pandas and the scientific Python stack
• Experience designing libraries other people depend on
• Strong testing practice including numerical tolerance testing
• Proficiency with SQL and time series data storage
• Understanding of profiling and performance optimization in Python
• Familiarity with packaging, virtual environments and continuous integration
• Ability to work directly with researchers and translate needs into tools

Preferred Qualifications

• Experience with Cython, Numba or writing C extensions
• Exposure to Dask, Ray or another distributed compute framework