Product Manager

NBCUniversal•New York, NY

2d•Hybrid

About The Position

The Product Manager, Enterprise Data & AI will be part of NBCUniversal’s Enterprise Data + AI Product organization, turning business problems into products, solutions and experiences that create measurable value. This hands-on product-building role sits at the intersection of business, product, data and AI. The Product Manager partners with business and product teams to understand workflows, uncover problems and opportunities, connect needs to enterprise capabilities, and move ideas from discovery through validation and adoption. The role calls for strong product judgment, business curiosity, technical fluency and a bias toward action. The Product Manager will work with stakeholders to shape use cases, build or prototype solutions with modern tools, develop product narratives, and measure whether experiences create value. It is not limited to managing a feature backlog; it involves operating in ambiguity, taking ownership, and using technology—particularly AI—to help turn ideas into meaningful business outcomes.

Requirements

Bachelor’s degree or equivalent practical experience.
At least 5 years of experience in Product Management, Product Strategy, technical Product Marketing, MarTech/AdTech, Solutions, Data/AI products, customer-facing technology or a related product and technology discipline.
Demonstrated ability to take an ambiguous customer or business problem from discovery through a clear product opportunity, solution or measurable outcome.
Strong product judgment and customer-discovery skills, including the ability to challenge a stated request and uncover the underlying business need.
Strong data fluency and comfort working with analytics, metrics, data products and technical concepts.
Hands-on experience using AI-assisted development, prototyping or automation tools to create working prototypes, workflows or other tangible solutions.
Ability to translate complex technical concepts into clear, compelling and actionable guidance for technical and non-technical audiences.
Strong stakeholder management and cross-functional leadership skills, including the ability to influence without formal authority.
Ability to operate independently, create structure from ambiguity and drive work from problem through outcome with minimal oversight.
Excellent written, verbal and visual communication skills.

Nice To Haves

Experience with enterprise data platforms, MarTech, AdTech, identity, CRM, analytics, AI platforms or other data-intensive product environments.
Experience with GitHub Copilot; experience with Claude Code, Cursor or similar AI development environments is also valuable.
Experience building prototypes, lightweight applications, automations or agentic workflows without relying exclusively on an Engineering team.
Experience developing product positioning, go-to-market strategies, demonstrations, enablement or adoption programs for technical products.
Experience establishing Voice of the Customer, customer-success, product usage or adoption feedback loops.
Familiarity with GitHub, Jira, Confluence, Figma and analytics or BI platforms.
Builder mentality, with a bias toward experimentation, learning and tangible outcomes.
Intellectual curiosity and willingness to rapidly learn unfamiliar business and technical domains.
Strong ownership and follow-through, with a proactive approach to identifying gaps and moving work forward without waiting for perfect clarity.
Ability to move between strategy and execution, from senior-level business conversations to hands-on building and problem solving.

Responsibilities

Build trusted relationships with enterprise stakeholders, understand their workflows, and uncover problems, opportunities and unmet needs.
Translate stakeholder needs into use cases, product opportunities, hypotheses and measurable outcomes, connecting them to existing enterprise products and capabilities where possible.
Use AI-assisted development, prototyping and workflow tools to create tangible solutions, test assumptions and accelerate learning and decision-making.
Develop product positioning, demonstrations, enablement materials and engagement motions that support understanding, adoption and successful use.
Establish feedback loops using stakeholder input, qualitative insights, usage signals and business outcomes to identify friction and opportunities for improvement.
Define and track measures of adoption, engagement and business value, using quantitative and qualitative data to inform decisions.
Bring business, customer and adoption insights to Product Managers and product leaders to inform roadmap priorities, investment decisions and portfolio direction.
Partner across Product Management, Product Operations, Engineering, Data, AI and business teams to move opportunities toward scalable solutions without relying on formal authority.
Make complex data, technology and AI capabilities understandable through clear narratives, demos, executive-ready materials and reusable enablement assets.
Apply AI in discovery, research, analysis, prototyping, documentation and workflow automation, and identify opportunities to increase organizational leverage and self-service.
Communicate across business, Product, Data, Engineering and AI teams.