Product Developer – Commodities And Multi-Asset

In this role you will design, backtest, implement and enhance Bloomberg's multi-asset indices, with a focus on commodities within diversified strategies. You will bridge research, product and engineering to deliver scalable, production-ready index and QIS solutions across asset classes. Collaborating with data, engineering and client-facing teams, you help translate requests into robust capabilities and rigorous data-driven decisions. The role offers impact in shaping commodity exposures and systematic benchmarks at scale, within a collaborative, technically rigorous environment.

• Design, backtest, and implement multi-asset, risk-premia and QIS methodologies with commodity components
• Identify and mitigate backtesting biases and ensure robust validation
• Source, validate, and map market data inputs across systems, including commodity futures and curve data
• Assess technical constraints and automation needs early in ideation
• Collaborate with Engineering to automate indices and strategies for production
• Refine client requests into feasible implementation plans and support sales interactions
• Contribute to internal tooling and reusable index frameworks
• Support governance and documentation in line with regulatory standards
• Communicate complex quantitative concepts to both technical and non-technical audiences
• Work with cross-functional teams across Data, Enterprise Data and Risk & Compliance, and present to clients

• 5+ years in index development, QIS, systematic strategies or related product development
• Strong quantitative capability and financial markets understanding
• Hands-on experience building and validating end-to-end systematic index backtests or quantitative strategy simulations
• Strong understanding of commodities (futures, term structure, roll yield) and their role in multi-asset portfolios
• Familiarity with multi-asset derivatives and risk-premia (carry, trend, curve)
• Strong Python proficiency with clean, modular, testable code
• Experience with large datasets and translating research into production
• Clear communication and ability to translate client requests into implementations
• Working knowledge of benchmark regulations and governance for index events

• Clear communicator
• Collaborative mindset
• Creative and proactive problem-solver
• Python
• Data analysis and backtesting
• Portfolio construction concepts