Product Developer – Commodities And Multi-Asset

Overview

In this role you will help design, backtest, and implement Bloomberg’s Multi-Asset indices with a focus on commodities within diversified strategies. You’ll work at the intersection of research, product, and engineering to deliver scalable, production-ready index and QIS solutions. You’ll translate client requests into implementation plans and collaborate with data, engineering, and risk teams to ensure robust, automated solutions. The role emphasizes data-driven decision making, regulatory awareness, and delivering impactful, market-relevant benchmarks.

Responsibilities

• Design, backtest, and validate multi-asset, risk-premia and QIS methodologies with commodity components
• Source and map market data inputs across systems, including commodity futures and curve data
• Collaborate with Engineering to implement and automate indices and strategies
• Refine client requests into implementable plans and assess feasibility
• Contribute to internal tooling and reusable index frameworks
• Support governance and documentation in line with regulatory standards
• Communicate complex quantitative concepts to diverse audiences
• Identify and mitigate backtesting biases and ensure scalability in ideation and production

Key requirements

• strong quantitative academic background in a quantitative discipline
• 5+ years in index development, QIS, or related product development
• hands-on experience building end-to-end systematic index backtests or strategy simulations
• strong understanding of commodities and multi-asset derivatives (carry, trend, curve)
• strong Python proficiency for clean, modular code
• experience with large datasets
• knowledge of financial markets and portfolio construction concepts
• experience collaborating with Engineering to translate research into production systems
• clear communication skills and ability to translate client requests into implementation plans
• working knowledge of benchmark regulations and governance for index events

• clear communication
• collaboration across teams
• creativity and enthusiasm
• Python
• SQL (familiarity)
• data handling and large datasets

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