Quant Developer

The Quant Developer is a specialist role within the Risk Department, responsible for developing quantitative applications and analytical tools that underpin the Exchange's risk management and settlement pricing processes. Unlike a traditional software engineering role, this position focuses on implementing risk methodologies, pricing models, market data controls and automation solutions that support the daily operation of the clearing house and its risk framework. 

The successful candidate will work closely with risk professionals to translate quantitative methodologies into reliable, configurable and auditable systems, ensuring accurate risk calculations, high-quality market data and robust operational controls across the risk management lifecycle. 

Key Responsibilities 

• Develop Python-based applications for risk management, settlement pricing and process automation. 

• Automate risk calculations, reconciliations, monitoring and reporting. 

• Build a DSP system covering market-data ingestion, pricing waterfalls, validation rules, exceptions and approvals. 

• Translate approved pricing methodologies into configurable and auditable system rules. 

• Develop controls for stale, erroneous, illiquid or unrepresentative market data. 

• Build tools for statistical analysis, backtesting, historical replay and exception monitoring. 

• Maintain appropriate testing, documentation, access controls, audit trails and GitHub repositories. 

• Work closely with Risk, Market Operations, Clearing Operations and Technology teams. 

• Maintain database to support risk and pricing system 

Requirements 

• Degree in Mathematics, Applied Mathematics, Statistics, Financial Engineering, Computer Science, Physics, Engineering or a related quantitative discipline. A Mathematics degree is preferred. 

• 5+ years of professional Python development experience required, preferably within a financial institution, exchange, clearing house, trading firm or fintech company. 

• Strong knowledge of Python, SQL, statistics, time-series analysis and software-development practices. 

• Experience with financial market data, pricing, risk analytics or quantitative systems. 

• Understanding of futures, derivatives, settlement pricing, market liquidity and contract spreads would be advantageous and can be developed on the job. 

• Strong analytical, problem-solving and communication skills. 

• Strong knowledge of AWS services and hands-on experience integrating cloud-native solutions. 

• Experience with containerization technologies (e.g., Docker) and orchestration platforms such as Kubernetes (K8s). 

• Understanding of software security principles, including identification and remediation of vulnerabilities. Experience with vulnerability scanning tools, dependency management (e.g., npm/pnpm audit), and applying patches or mitigations