As a Python Risk Developer, you will sit at the intersection of quantitative research, risk management, and software engineering. You will be responsible for designing, building, and maintaining the core pricing and risk infrastructure used by senior management and portfolio managers across multiple asset classes (including equities, macro, and credit). You will ensure that our global risk models are accurate, highly performant, and deeply integrated into our daily trading lifecycle.

Key Responsibilities:

* Risk Infrastructure Engineering: Design, build, and optimize robust Python-based risk engines, pricing libraries, and data pipelines to support intra-day and end-of-day risk reporting.

* Model Implementation: Collaborate closely with Quantitative Researchers and Risk Managers to implement, backtest, and productionalize mathematical risk models (e.g., VaR, stress testing, scenario analysis, and factor models).

* Cross-Asset Support: Develop framework features capable of handling a diverse set of financial instruments, ensuring seamless risk aggregation across regional portfolios.

* Performance Tuning: Optimize data processing pipelines handling massive datasets, using tools like NumPy, Pandas, or parallel computing frameworks to minimize latency.

* System Integration: Integrate risk tools with internal portfolio management platforms, order management systems (OMS), and external market data providers.