Bloomberg

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, balancing new development, product quality, technical investment and client commitments. 
• Collaborate with data, engineering, sales, implementation, support and other product teams to deliver products and resolve execution risks. 
• Ensure that products meet the needs of sophisticated research and production workflows, including use through APIs, cloud platforms, programming languages and other enterprise delivery channels. 
• Work with adjacent Bloomberg teams to improve consistency and interoperability across macro, commodity, pricing, reference and alternative data. 
• Support sales and client-facing teams with product expertise, market context, demonstrations and clear articulation of product value. 
• Monitor developments in macroeconomic and commodity markets, quantitative investment research, AI-enabled workflows, financial data infrastructure and the competitive data landscape. 

You will need to have 

• A minimum of five years’ experience in product management, financial data, investment research, quantitative research, data analysis or a related role. 
• Knowledge of macroeconomic or commodity markets, preferably including experience with one or more of the following: economic indicators, surveys, government auctions, rates, foreign exchange, futures, energy, metals, agriculture, commodity balances, physical flows, positioning or alternative data. 
• Familiarity with quantitative, systematic or data-driven investment research, including how datasets are evaluated, combined and used in signal development, forecasting, backtesting or portfolio analysis. 
• Experience gathering client or user requirements and translating complex workflows into clear product or technical specifications. 
• Commercial judgement and an understanding of how product value is converted into adoption and revenue through effective positioning, packaging and pricing. 
• Strong analytical and problem-solving skills, including the ability to assess market opportunities, evaluate trade-offs and make evidence-based recommendations. 
• The ability to manage multiple priorities and coordinate delivery across product, data, engineering, sales and support functions. 
• Strong written and verbal communication skills, with the ability to explain complex data and market concepts to technical and non-technical audiences. 
• Familiarity with modern data platforms, APIs and cloud-based data delivery. 
• Working proficiency in Python, R, SQL or another language commonly used in data analysis, quantitative research or data engineering. 
• A bachelor’s degree or equivalent professional experience in economics, finance, statistics, mathematics, computer science, engineering, business or a related discipline. 

We use years of experience as a guide and will consider candidates who can demonstrate the domain expertise, product judgement, commercial awareness and technical capabilities required for the role.