What You'll DoYou'll work with clients to turn their enterprise data vision into a defined, sequenced, and communicated plan of record:
- Own product definition for the data portfolio - reporting and analytics, privacy-by-design, segmentation, predictive models, and the platform capabilities underneath them.
- Maintain the roadmap: a rolling view of what the data team is delivering across the next two to three quarters, kept current, and defensible to any executive who asks why something sits where it does.
- Write the product vision documents, acceptance criteria, and release notes that let engineers build without guessing and let stakeholders know what they are getting.
- Define what success looks like for every product, instrument it, and report on it - usage, adoption by department, time to insight, model performance in production, and the business result it was built to move.
- Say plainly when something isn't working, and change or retire products that don't earn their usage.
- Run the planning and execution rhythm: monthly planning, standups, and the working agreements that keep a small senior team moving on a Kanban flow.
- Keep BAU visible and bounded so it doesn't quietly consume delivery capacity.
- Sit with every function that touches fan, revenue, or venue data, understand what each is trying to accomplish, translate that into data product requirements, and close the loop when something ships.
- Serve as the standing connection between the data team and the rest of PS&E.
- Write status that executives can read in one pass, launch communications that drive adoption, and documentation that makes the portfolio legible to people who weren't in the room.
Requirements
- Seven or more years in product management, with meaningful time on data, analytics, or platform products.
- Experience with a modern data stack, enough to hold a credible conversation with engineers about tradeoffs without needing to write the code.
- Demonstrated ability to run planning and delivery for a technical team, and a track record of setting and reporting on product metrics rather than tracking output.
- Strong written communication, specifically the ability to write for executives.
- Working fluency with AI tooling in daily practice.
- A track record of taking data products from vision to adoption.
Bonus Experience- Sports, entertainment, media, or consumer businesses with large customer bases.
- Defining AI-enabled product capabilities - conversational access to data, agent-driven insight delivery, or models embedded in business workflow.
- Privacy-by-design or data governance as part of a product you owned.
- Customer segmentation or predictive models.
- Kanban delivery with a monthly planning cadence.
If you've taken data products from a vision document all the way to people actually using them, we'd like to talk. Apply today!
