removing manual steps and operational risk.Convert existing R research code to Python, preserving numerical equivalence while improving structure, testing, and maintainability.Take research models, backtesting frameworks, and analytics into production, and develop the Python research infrastructure used daily by the team — with proper version control, monitoring, data quality controls, and rising … understanding of capital markets — instruments, market structure, and the data that describes them.Some exposure to quantitative research concepts such as return forecasting, factor models, backtesting, portfolio construction, or statistical inference on financial data.Fluency with modern engineering practice, including version control, automated testing, continuous integration, code review, and reproducible environments.A clear ...