Python Risk Developer

IO Tech Solutions Limited; Hong Kong; On-site; HKD 600,000 - 1,200,000; Full time

Job summary

IO Tech Solutions Limited in Hong Kong seeks a Python Risk Developer to design, build, and maintain core pricing and risk infrastructure across multiple asset classes. You will work with senior managers and portfolio teams to ensure accurate, high-performance risk calculations.

The role emphasizes implementing risk models (VaR, stress testing), data pipelines, and seamless integration with trading workflows. Strong Python, NumPy, and Pandas skills are essential.

Qualifications

• Strong Python programming and software engineering skills.
• Experience implementing risk models and pricing infrastructure.
• Familiarity with risk concepts (VaR, stress testing) and cross-asset risk aggregation.
• Experience optimizing data pipelines and handling large datasets (NumPy, Pandas).

Responsibilities

• Design, build, and optimize Python-based risk engines, pricing libraries, and data pipelines for intra-day and end-of-day risk reporting.
• Collaborate with Quant researchers and Risk Managers to implement, backtest, and productionize mathematical risk models (VaR, stress testing, scenario analysis).
• Develop framework features for cross-asset risk aggregation across regional portfolios.
• Tune performance of data processing to minimize latency in large datasets using Python tooling.
• Integrate risk tools with internal PM platforms, OMS, and external data providers.

Skills

Python

NumPy

Pandas

Performance tuning

Parallel computing

Tools

Data pipelines

Job description

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.