Data & AI Product Manager

About the role

TKO Group Holdings, Inc. (NYSE: TKO) is a premium sports and entertainment company owning UFC, WWE, PBR, IMG, On Location, reaching 1 billion households across 210 countries, organizing >500 live events yearly, >3 million fans. The Data & AI Products & Services (DAPS) team builds a trusted data and AI foundation for brands and enterprise functions. The Data & AI Product Manager will own data products supporting On Location across commercial, customer, event, marketing, finance, sales, and operational use cases, translating business needs into reusable data products, guiding engineering and data teams, ensuring adoption, trust, measurability, and continuous improvement.

Responsibilities

• Own product direction, roadmap, backlog, and lifecycle for On Location Base data products (customer and transaction data, commercial reporting, marketing and audience activation, lead scoring, attribution, commissions, 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.
• 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 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.

Requirements

• 3+ years of experience in data product management, technical product management, analytics product management, data engineering, data science, analytics engineering, or a closely related field.
• Strong technical foundation in at least one of: data engineering, software engineering, data science, analytics engineering, or data analysis – with ability to reason credibly about the others.
• Experience translating business problems into data models, analytical products, platform capabilities, integrations, APIs, pipelines, or AI‑enabled workflows.
• Working fluency with SQL and modern data concepts such as dimensional modeling, data quality, identity resolution, semantic layers, event instrumentation, warehouse/lakehouse architecture, APIs, and data lifecycle management.
• Demonstrated ownership of products or complex initiatives from discovery through delivery, launch, adoption, and ongoing operation.
• Strong execution and operating discipline: keep commitments visible, follow up on dependencies, surface risks early, close loops.
• Excellent written and verbal communication, including ability to explain technical tradeoffs and data limitations to senior business leaders.
• Experience balancing multiple concurrent priorities in an environment with changing requirements, hard dead