Product Developer – Commodities And Multi-Asset

Bloomberg is hiring a Product Developer – Commodities And Multi-Asset in London, United Kingdom. Level rates it ; you can apply on Level.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
Level files it as a senior role.
Level lists 337 other open roles at Bloomberg.
The role was posted in the last few days.

AI in this role

Bloomberg is a leading provider of financial benchmarks and custom index solutions. Strategy indices have become central to capital markets, powering ETFs, structured products, derivatives, and institutional mandates. As regulatory frameworks evolve and investor demand for systematic and rules-based solutions grows, we are expanding our Multi-Asset Product Development team.
This is an opportunity to join a highly collaborative and technically rigorous team within Bloomberg's Enterprise Data Products Group, focused on building scalable, systematic index solutions across asset classes.
What's the Role?
You will join Bloomberg's Multi-Asset Product Development team, where you will contribute to the design, backtesting, implementation and ongoing enhancement of Bloomberg's Multi-Asset indices, with a focus on the role of commodities within multi-asset allocation, risk-premia and QIS strategies.
This role sits at the intersection of research, product, and engineering. You will work on index and QIS methodologies on commodities but also spanning equities, rates, FX and credit ensuring they are scalable, robust, and aligned with both client needs and platform capabilities. You will help shape how commodity exposures, from carry and roll strategies to curve and trend premia, are built into diversified multi-asset and risk-premia products.
You will help support research-driven innovation, translate client requests into implementable index and QIS solutions, and partner with Engineering and Production teams to ensure strategies are automated and production-ready. You will also contribute to systematic data assessments, evaluating new datasets for fit-for-purpose use in benchmarks. This covers methodology, historical behavior, coverage and mappings, limitations of use, and the controls and platform requirements for onboarding. You will turn your findings into clear requirements that move through dedicated data working groups and into production. You will adapt your communication style to your audience and be equally adept at collaborating closely with colleagues across multiple teams, including Data, Enterprise Data and Risk and Compliance, as well as presenting to clients and soliciting feedback. You’ll be comfortable working with large and complex data sets, ideally with quantitative or data science skills (e.g., Python), and have a gift for extracting meaningful intelligence to drive innovation, product direction and data-driven decisions.
This role requires strong quantitative capability, technical fluency, commercial awareness, and a mindset focused on scalability and execution discipline. You'll be someone with the ability to approach challenges with creativity and enthusiasm; someone who has the courage to take positions advocating change and then deliver.
Regarding domain expertise, you'll understand trends in the index and QIS business, regulation, and what our customers need. You'll also be keen to learn more.
We'll trust you to:

Communicate complex quantitative concepts clearly to both technical and non-technical audiences
Design, backtest, and validate multi-asset, risk-premia and QIS methodologies with commodity components
Identify and mitigate backtesting biases (e.g., survivorship bias, look-ahead bias, overfitting)
Source, validate, and map market data inputs across multiple systems, including commodity futures and curve data
Evaluate technical constraints, automation requirements, and scalability early in the ideation process
Partner closely with Engineering to implement and automate indices and strategies efficiently
Work with Sales and clients to refine custom index and QIS requests, including commodity-linked requests, and assess feasibility
Contribute to improving internal tooling and reusable index frameworks
Support documentation and governance processes in line with regulatory standards

You'll need to have:

A strong academic background in a quantitative discipline including, but not limited to, Finance, Engineering, Mathematics, Physics, Computer Science, Statistics, or Economics
5+ years of experience in index development, QIS, systematic strategies, quantitative analysis, or a related product development role
Hands-on experience building and validating end-to-end systematic index backtests or quantitative strategy simulations
Strong understanding of the commodities asset class, including futures term structure dynamics, roll yield, and sector-specific characteristics (Energy, Metals, Agriculture), and of how commodities behave within diversified multi-asset portfolios
Strong understanding of multi-asset derivatives and systematic strategy design (e.g., futures, options, swaps), including risk-premia such as carry, trend, and curve
Strong Python proficiency, with experience writing clean, modular, testable code
Ability to independently prototype an index or strategy from an idea, to a validated backtest, to a product specification
Experience working with large datasets
Strong understanding of financial markets
Familiarity with portfolio construction concepts and factor-based investing
Solid understanding of backtesting methodology and common pitfalls
Experience collaborating with Engineering teams to translate research into production systems
Clear communication skills and the ability to translate client requests into structured implementation plans
Working knowledge of benchmark regulations (e.g., BMR, IOSCO principles) and day-to-day governance determinations for index events

We'd like you to have:

Experience with SQL and structured data environments
Familiarity with performance optimization and vectorized computation
Hands-on experience applying optimizers to portfolio construction (e.g., mean-variance, risk-budgeting, constrained optimization), including handling of constraints and turnover
Exposure to QIS products distributed through banks, including familiarity with the structures and payoffs they are typically embedded in
Understanding of how indices and QIS are monetized (ETFs, structured products, licensing)
Experience with version control tools (e.g., Git)

If indicated, please note that years of experience are a guide; we will consider applications from all candidates who can demonstrate the skills necessary for the role. Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

How we rate this

Product Developer – Commodities And Multi-Asset at Bloomberg rates 63 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Product Developer – Commodities And Multi-Asset is an open job at Bloomberg.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in London, United Kingdom.
The job was posted on October 19, 2026.
Seniority: senior.
Applications are handled by Bloomberg. Apply on Bloomberg

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