Level

Bloomberg

Product Manager, Alternative Data - Data Feeds

AI in this role

databricks
Who we are:The Bloomberg Alternative Data team is a fast-growing, high-impact product group building the next generation of data and analytics for company research and intelligence. Our mission is to make alternative data as essential to investment workflows as traditional fundamentals — at global scale.
What's in it for you:Bloomberg's Alternative Data team is seeking a Product Manager to own the end-to-end lifecycle of our data feed products. In this role, you will be the primary product owner for Bloomberg's alternative data feed products, setting the strategy, driving new product development, and taking direct accountability for a critical growth area at Bloomberg.
Bloomberg is uniquely positioned to address client needs leveraging alternative data for company research in the age of AI. In this role you will help shape and transform the future of investment research, with high visibility from engineering leadership to buy-side clients and a direct line of sight to commercial outcomes.
We’ll trust you to:
  • Own product strategy and roadmap: Define, prioritize, and evangelize the what and the why behind our data feed offerings — identifying new product opportunities, evaluating whitespace, and translating business goals and opportunity into a technical roadmap in close partnership with engineering
  • Drive commercial outcomes: Share accountability for revenue and growth metrics for the feeds you own; support pricing, packaging, and competitive positioning decisions in partnership with GTM teams
  • Deeply understand our clients: Empathetically understand the business, workflows, and objectives of our target users — including fundamental, quantitative, and systematic investors — and the specific ways they leverage alternative data for signal generation, backtesting, and investment research
  • Own data quality and operational reliability: Take product-side accountability for the accuracy, stability, and delivery consistency of your feeds — partnering with engineering and data science on QA frameworks including automated QA systems, outlier detection, and coverage checks; own incident communication and data issue escalation workflows
  • Drive cross-functional execution: Collaborate with sales, marketing, customer support, engineering, and data science to bring data feed products to market and drive client engagement at scale
  • Lead your Agile team: Serve as product owner to your engineering team — setting development priorities, balancing functional and technical requirements, managing the backlog, and writing precise, implementation-ready PRDs
  • Define success metrics: Establish and monitor metrics for engagement, data health, and business impact across products and features
  • Manage data vendor relationships: Deeply understand the underlying data and manage key third-party data vendor relationships, including evaluating new data partnerships for coverage, quality, and licensing implications

You'll need to have:
  • 5+ years of product experience with data-intensive, data feed, or B2B data products
  •  Deep understanding of alternative data use cases and institutional investor workflows — including how quant, fundamental, and systematic investors leverage transaction-level, consumer, and B2B spend data for signal testing, backtesting, and alpha generation
  • Hands-on experience working with data, including familiarity with data quality, QA practices, and the operational realities of delivering high-reliability data products
  • Demonstrated commercial accountability — you've had direct line of sight to revenue, ARR, or P&L outcomes for a product you owned, and have made decisions that measurably impacted commercial results
  • Demonstrated ability to write implementation-ready PRDs and manage complex delivery processes across multiple teams
  • Experience working directly with data engineers, data scientists, and cross-functional stakeholders across large organizations
  • Strong client-facing communication skills; comfortable on sales calls and managing client escalations
  • Strong organizational skills and the ability to manage multiple concurrent initiatives without losing sight of delivery timelines

We'd love to see:
  • Familiarity with Bloomberg data products, the Bloomberg Terminal, or enterprise data delivery platforms (e.g., Snowflake, Databricks)
  • Exposure to data delivery infrastructure: APIs, flat files, cloud storage, portal-based delivery
  • Demonstrated working knowledge of applying alternative data to surface investment opportunities or answer investment research questions
  • Experience managing or partnering on third-party data vendor relationships
  • You've successfully executed in large company settings, collaborating across multiple stakeholders to bring scaled products to market

Salary Range = 140,000 - 295,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.


We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
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How we rate this

Product Manager, Alternative Data - Data Feeds at Bloomberg rates 8 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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.

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