Lead Product Manager at NBCUniversal3

As Lead Product Manager in Product Management — Data Analytics, you will define and execute the vision, strategy, and roadmap for analytics and data products that power decision-making and performance across Ad Sales. This role requires a hands-on, highly technical product leader who is fluent in data engineering concepts, relational modeling, AI/ML applications, and enterprise analytics platforms. You will translate complex business needs into scalable data products, collaborating closely with data engineering, platform teams, and business stakeholders to transform multi-source datasets into actionable, self-service insights. Key Responsibilities Product Strategy & Roadmap • Define and socialize a long-term strategy and outcome-based roadmap for analytics and data products aligned with Ad Sales priorities and NBCU technology standards. • Explore and evaluate internal/third-party datasets; shape analytical tools, AI-enabled insights, and scalable data products that deliver measurable business impact. • Drive innovation by identifying emerging technologies, data patterns, and opportunities to improve decisioning, automation, and predictive intelligence across the Ad Sales ecosystem.Solution Delivery • Translate business needs into clear, technically sound product requirements, functional specifications, user stories, KPIs, and measurable success criteria. • Work hands-on with data—querying datasets, validating logic, understanding source-to-target mappings, entity relationships, and data transformation flows. • Lead discovery and prototyping initiatives to validate concepts; partner with architecture, platform, and data engineering teams to build and deploy data pipelines, AI/ML models, and BI products. • Ensure quality, reliability, and scalability across ingestion, modeling, orchestration, and visualization layers.Program & Project Leadership • Plan and manage execution for complex cross-functional initiatives; identify, track, and communicate milestones, dependencies, and risks across globally distributed teams. • Establish governance frameworks for backlog management, prioritization, release planning, and change management. • Uphold enterprise data governance, privacy, and security standards throughout the product lifecycle.Stakeholder Engagement & Adoption • Build strong partnerships with Sales Operations, Strategy, Finance, Marketing, and Engineering; translate user needs into product capabilities and ensure successful adoption via self-service enablement. • Communicate strategy, progress, and business outcomes to leadership through compelling storytelling and data-driven insights. • Drive continuous improvement by synthesizing feedback, telemetry, usage analytics, and performance trends.Team Leadership • Coach and mentor product managers, analysts, and technical team members; foster a collaborative, experimentation-oriented culture focused on excellence and accountability. • Create alignment across engineering, business stakeholders, and leadership around vision, priorities, and delivery expectations.