Python Risk Engineer

Key Responsibilities Risk Engine Development: Design, build, and maintain scalable risk platforms, valuation engines, and P&L attribution frameworks using Python.API & Integration: Build and support robust REST APIs that interface internal scenario eng Model Implementation: Translate complex quantitative risk models (e.g., Credit Risk, Market Risk, and Greeks) from prototypes or spreadsheets into optimized, production-level libraries. Data Pipelines & Automation: Create automated ETL workflows to ingest, clean, and process massive financial datasets and real-time market data. Database Management: Write, optimize, and maintain complex SQL queries to interact with transactional and historical data layers. Cross-Functional Collaboration: Partner with the business, risk managers, and quants to convert complex scenario testing and risk workflows into technical requirements. Required Technical Skills Financial Background: 4+ years of professional experience working within financial services, investment banking, hedge funds, or asset management environments. Core Python Expertise: Advanced proficiency in writing clean, modular, and performant Python code (Object-Oriented Programming, concurrency, memory optimization). Data Management: Strong knowledge of SQL relational databases (PostgreSQL, SQL Server) and experience managing large financial datasets. Development Tools: Proficiency with Git version control, CI/CD pipelines, and writing comprehensive unit tests. System Architecture: Understanding of backend frameworks (like FastAPI or Flask) and system performance optimization techniques. Open for both Hong Kong and Singapore Applicants.