Data & AI Product Manager

About the role

The Opportunity TKO is building a trusted data and AI foundation that helps its brands and enterprise functions understand the business, make better decisions, and act with greater speed and precision. The Data & AI Product Manager will own a portfolio of data products and capabilities that support On Location, TKO’s sports and entertainment hospitality business, across commercial, customer, event, marketing, finance, sales, and operational use cases. This is a hands-on product management role for someone who can move comfortably between business outcomes and technical implementation. You will translate complex needs into reusable data products, guide TKO engineering and data teams through delivery, and make sure the capabilities we launch are adopted, trusted, measurable, and continuously improved. The role sits within DAPS, the cross-TKO Data & AI Products & Services organization, and partners closely with the On Location technology organization. You will help enable reporting and decision-making across a changing portfolio of major events and businesses - including NCAA, Super Bowl, UFC, WWE, World Cup, and other On Location programs - while building patterns that can be reused across TKO.

Responsibilities

• Own the product direction, roadmap, backlog, and lifecycle for On Location Base data products, including customer and transaction data, commercial reporting, marketing and audience activation, lead scoring, attribution, commissions, and operational analytics.
• Oversee development of reusable data products on Snowflake, including dimensional models, curated data sets, semantic definitions, data interfaces, and governed self-service assets.
• Partner with analytics and business teams to shape BI reporting and AI-enabled capabilities that solve real business problems and turn event-specific needs into reusable patterns where appropriate.
• Act as a trusted advisor to stakeholders across product, pricing strategy, marketing, finance, sales, operations, guest/customer experience, and event leadership.
• Shape unmet needs into opportunities with a clear user, decision, action, value hypothesis, success measure, dependencies, and stop/reconsider criteria.
• Manage a visible multi-horizon portfolio, making tradeoffs across business value, urgency, risk, reuse, delivery confidence, capacity, and displaced work.
• Convert product intent into clear Jira epics, stories, acceptance criteria, data contracts, measures, and decision records.
• Partner day-to-day with TKO data engineering, analytics engineering, data science, platform, governance, security, and external delivery teams to move work from discovery through production.
• Keep dependencies, milestones, risks, decisions, blockers, stakeholder commitments, launch readiness, adoption, and post-launch ownership visible.
• Business stakeholders can clearly