Lead Product Manager

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.