Quant Developer (VaR)
Commodities Trading
London (hybrid)

Our client is a global commodities trading firm, and are seeking an experienced and hands-on Quant Developer with a strong background in building and enhancing Value-at-Risk (VaR) engines to join their team. The successful candidate will play a critical role in the development, implementation, and continuous improvement of our risk management systems, with a particular focus on VaR engines.

Key Responsibilities:

• Responsible for maintenance and enhancements of historical VAR engine.
• Develop and Enhance VaR Engines: Lead the design, development, and optimization of VaR engines. Reproduce existing engines with a focus on performance improvements and scalability, ensuring they meet the evolving needs of the business.
• Hands-on Development: Engage in full-stack development, from data ingestion and processing to building high-performance, distributed computing systems. Your work will directly impact the accuracy and efficiency of the firm's risk management capabilities.
• Performance Tuning and Optimization: Continuously monitor, analyze, and improve the performance of VaR engines, ensuring low-latency and high-throughput processing. Implement enhancements that improve the speed, accuracy, and reliability of risk calculations.
• Collaborate with Cross-functional Teams: Work closely with risk managers, quants, and other developers to understand requirements and deliver solutions that meet business needs. Provide technical leadership and mentorship to junior developers as needed.

Requirements:

• Proven Experience: 5+ years of hands-on development experience, with a focus on building risk management systems, particularly VaR engines. Strong background in working with large-scale, high-performance computing environments.
• Programming Expertise: Advanced programming skills in Python, with a strong emphasis on performance optimization and distributed computing. Experience with other relevant languages (eg, C++, Java) is a plus.
• Risk Management Knowledge: Solid understanding of market risk principles and the mechanics of VaR models. Prior experience with financial systems, particularly in commodities or other asset classes, is highly desirable.