Product Manager, Quantitative Data Solutions

Macro and Commodity Research Data 

Bloomberg is building a comprehensive suite of normalized, linked and point-in-time datasets for quantitative, systematic and quantamental investment research. The portfolio brings together company fundamentals, estimates, pricing, supply-chain relationships, industry and segment-level data, macroeconomic indicators, commodity supply and demand data, and alternative data through interoperable products designed for research and production workflows. 

We are establishing a new Macro and Commodity Research Data vertical and are looking for an experienced Product Manager to help build and develop its product portfolio. 

This role requires an understanding of FX, Rates or commodity markets, the data used to analyse them, and the workflows through which investment managers turn data into signals, forecasts, portfolio decisions and risk views. The successful candidate will also understand how AI, modern research tools and data infrastructure are changing the way clients discover, evaluate and consume financial data. 

You will work on products spanning areas such as economic releases, auctions, prediction markets, macro risk factors, commodity supply & demand, physical flows, positioning, outages and other market-relevant datasets. You will help identify where Bloomberg can create differentiated client value, translate research workflows into product requirements and support the commercial development of the portfolio. 

The Research Data business is an important part of Bloomberg Enterprise Data’s growth strategy. Our objective is to solve complex research and data-management problems for quantitative, systematic and fundamental investment teams, while making Bloomberg data easier to discover, evaluate, integrate and use across client workflows. 

We will trust you to 

• Own the development and ongoing management of products within the Macro and Commodity Research Data portfolio, from initial opportunity assessment through launch, adoption and continued enhancement. 
• Develop strong subject-matter expertise in relevant macroeconomic or commodity datasets and understand how they are used across systematic macro, commodities, multi-asset and fundamental investment workflows. 
• Work with clients, including researchers, portfolio managers, analysts, data scientists and data engineers, to understand their workflows, identify unmet needs and validate proposed solutions. 
• Translate client and market requirements into clear product specifications, including requirements for point-in-time integrity, historical depth, timestamps, revisions, identifiers, metadata, lineage, accessibility and interoperability. 
• Evaluate new product opportunities by considering client demand, competitive differentiation, market size, revenue potential, development effort and strategic fit. 
• Contribute to commercial strategy, including client segmentation, product positioning, packaging, pricing and monetisation. 
• Develop business cases for new products and enhancements, using client evidence, market analysis, expected adoption and commercial potential to support investment decisions. 
• Define product objectives and success measures, monitor adoption and usage, and use evidence to recommend changes to the product roadmap. 
• Manage product priorities, specifications and backlogs, bala