Description

  Productdefinition for the data portfolio.Reporting and analytics, privacy-by

design,segmentation, predictive models, and the platform capabilities underneath

them. 

·      Theroadmap. A rollingview of what the data team is delivering across the next two

tothree quarters, kept current, and defensible to any executive who asks why

somethingsits where it does.

·      Requirementsand definition of done.Writing the product vision documents,

acceptancecriteria, and release notes that let engineers build without guessing and

letstakeholders know what they\'re getting.

·      Outcomesand adoption.Defining what success looks like for every product in the

portfolio,instrumenting it, and reporting on it. Usage, adoption by department, time

toinsight, model performance in production, and the business result the product

wasbuilt to move. This role is accountable for knowing whether what we shipped is

workingand for saying so plainly when it isn\'t. Products that don\'t earn their usage

getchanged or retired.

·      Planningand execution rhythm.Running monthly planning, standups, and the

workingagreements that keep a small senior team moving on a Kanban flow.

KeepingBAU visible and bounded so it doesn\'t quietly consume delivery capacity.

·      Stakeholderalignment across the whole organization. Sitting with every function

thattouches fan, revenue, or venue data, understanding what each is trying to

accomplish,translating that into data product requirements, and closing the loop

whensomething ships. This role is the standing connection between the data team

and therest of PS&E.

·      Communication.Status thatexecutives can read in one pass. Launch

communicationsthat drive adoption. Documentation that makes the portfolio

legible topeople who weren\'t in the room.

AI-First Expectations

This role is expected to work the waythe rest of the team works. Use AI agents to draft

requirements, synthesize stakeholderinput, analyze usage data, and produce

documentation. The measure isthroughput and quality rather than hours spent. A person

in this seat should be operating atmultiples of a traditional PM\'s output because the

tooling allows it.

Beyond personal productivity, thisrole shapes how AI shows up in the products

themselves. Conversational access todata, agent-driven insight delivery, and models

embedded in business workflow are coreto the portfolio. The PM needs to be fluent

enough in what these systems can andcan\'t do to define them well.

Qualifications

·      Sevenor more years in product management, with meaningful time on data,

analytics,or platform products. 

·      Experiencewith a modern data stack, enough to hold a credible conversation with

engineersabout tradeoffs without needing to write the code. 

·      Demonstratedability to run planning and delivery for a technical team, and a track

recordof setting and reporting on product metrics rather than tracking output.

·      Strongwritten communication, specifically the ability to write for executives.

·      Workingfluency with AI tooling in daily practice.

·      Sports,entertainment, media, or consumer businesses with large customer bases

are aplus but not a requirement. The core requirement is someone who has taken

·      dataproducts from vision to adoption

Key Skills

Education

Any Gradute