Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
API @ 2
Communication @ 6
Data Analysis @ 3
Data Engineering @ 5
Mathematics @ 3
Product Management @ 3
Python @ 5
R @ 5
SQL @ 5
Statistics @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Bloomberg is building a comprehensive suite of normalized, linked and point-in-time datasets for quantitative, systematic and quantamental investment research. The portfolio includes company fundamentals, estimates, pricing, supply-chain relationships, industry and segment-level data, macroeconomic indicators, commodity supply and demand data, and alternative data for research and production workflows.
The Macro and Commodity Research Data vertical is seeking an experienced Product Manager to build and develop its product portfolio. The role requires knowledge of FX, rates or commodity markets, the data used to analyse them, and investment workflows involving signals, forecasts, portfolio decisions and risk analysis. The successful candidate will also understand how AI, modern research tools and data infrastructure are changing how clients discover, evaluate and consume financial data.
Responsibilities
- Own product development and ongoing management from opportunity assessment through launch, adoption and enhancement.
- Develop subject-matter expertise in macroeconomic and commodity datasets and their use in systematic macro, commodities, multi-asset and fundamental investment workflows.
- Work with researchers, portfolio managers, analysts, data scientists and data engineers to understand workflows, identify needs and validate solutions.
- Translate requirements into product specifications covering point-in-time integrity, historical depth, timestamps, revisions, identifiers, metadata, lineage, accessibility and interoperability.
- Evaluate opportunities based on client demand, competitive differentiation, market size, revenue potential, development effort and strategic fit.
- Contribute to product positioning, packaging, pricing, monetisation and commercial strategy.
- Define product objectives and success measures, monitor adoption and usage, and recommend roadmap changes.
- Manage priorities, specifications and backlogs while balancing development, quality, technical investment and client commitments.
- Collaborate with data, engineering, sales, implementation, support and product teams to deliver products and resolve execution risks.
- Support APIs, cloud platforms, programming languages and other enterprise delivery channels.
- Support sales and client-facing teams with product expertise, demonstrations and market context.
- Monitor macroeconomic and commodity markets, quantitative investment research, AI-enabled workflows, financial data infrastructure and the competitive data landscape.
Requirements
- At least five years of experience in product management, financial data, investment research, quantitative research, data analysis or a related role.
- Knowledge of macroeconomic or commodity markets, preferably including 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 signal development, forecasting, backtesting and portfolio analysis.
- Experience gathering client or user requirements and translating complex workflows into product or technical specifications.
- Commercial judgement and understanding of product positioning, packaging, pricing, adoption and revenue.
- Strong analytical, problem-solving, communication, prioritisation and coordination skills.
- Familiarity with modern data platforms, APIs and cloud-based data delivery.
- Working proficiency in Python, R, SQL or another language 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.
Compensation and Benefits
Salary range: $140,000–$295,000 USD annually, plus benefits and bonus. Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental and vision coverage, short- and long-term disability benefits, a 401(k) match, life insurance and wellness programs.