Product Manager

NBCUniversal•New York, NY

12d•$110,000 - $145,000•Hybrid

About The Position

The Product Manager, Enterprise Data & AI will be part of our Enterprise Data + AI Product organization and will help turn business problems into products, solutions and experiences that create measurable value across NBCUniversal. This is a hands-on product builder role at the intersection of business, product, data and AI. The Product Manager will work directly with business and product teams to understand how they work, uncover meaningful problems and opportunities, connect those needs to our enterprise capabilities, and help move ideas from discovery through validation and adoption. The ideal candidate combines strong product judgment with business curiosity, technical fluency and a bias toward action. You should be equally comfortable talking with a business stakeholder, understanding how a data or AI capability works, shaping a use case, building or prototyping a solution with modern tools, developing a clear product story and determining whether the resulting experience is creating value. This is not a traditional Product Manager role centered solely on managing a feature backlog. It is a role for someone who thrives in ambiguity, operates with high ownership and uses technology… particularly AI, to shorten the distance between an idea and a meaningful business outcome.

Requirements

Bachelor’s degree or equivalent practical experience.
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 turn ideas into working prototypes, workflows or other tangible solutions.
Ability to translate complex technical concepts into clear, compelling and actionable guidance for both technical and non-technical audiences.
Strong stakeholder management and cross-functional leadership skills with demonstrated ability to influence without formal authority.
Proven 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 strongly preferred; 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 modern product and collaboration tools such as GitHub, Jira, Confluence, Figma and analytics/BI platforms.
Builder mentality with a bias toward experimentation, learning and tangible outcomes over process for process’s sake.
Intellectual curiosity and willingness to rapidly learn unfamiliar business and technical domains.
Strong ownership mindset and follow-through; proactive driver who identifies gaps and moves work forward without waiting for perfect clarity.
Ability to move fluidly between strategy and execution — from senior-level business conversations to hands-on building and problem solving.

Responsibilities

Business discovery and stakeholder engagement to identify meaningful problems, opportunities and use cases
Translation of business needs into clear product opportunities, hypotheses, outcomes and success measures
Rapid prototyping and experimentation to make ideas tangible and accelerate learning
Product positioning, demos, enablement and other go-to-market motions that drive understanding and adoption
Voice of the Customer and product feedback loops that inform future priorities
Adoption and business-value measurement for priority initiatives
Clear communication between business, Product, Data, Engineering and AI teams
AI-enabled ways of working that increase speed, quality and individual leverage
Build trusted relationships with stakeholders across the enterprise, understand their workflows and proactively uncover problems, opportunities and unmet needs — including needs that may not initially be well articulated.
Translate stakeholder needs into clear use cases, product opportunities, hypotheses and measurable outcomes; connect those opportunities to existing enterprise products and capabilities whenever possible.
Use modern AI-assisted development, prototyping and workflow tools to rapidly bring ideas to life, test assumptions and create tangible experiences that accelerate learning and decision-making.
Develop the positioning, demonstrations, enablement materials and engagement motions necessary to help stakeholders understand, adopt and successfully use enterprise products and capabilities.
Establish structured feedback loops using stakeholder input, qualitative insights, usage signals and business outcomes to identify friction, unmet needs and opportunities for improvement.
Define and track appropriate measures of adoption, engagement and business value; use quantitative and qualitative data to tell a clear story and drive decisions.
Bring business, customer and adoption signal back to Product Managers and product leaders to help inform roadmap priorities, investment decisions and future portfolio direction.
Partner across Product Management, Product Operations, Engineering, Data, AI and business teams to determine the right path from opportunity to scalable solution without relying on formal authority.
Make sophisticated data, technology and AI capabilities understandable and actionable through clear product narratives, demos, executive-ready materials and reusable enablement assets.
Apply AI throughout discovery, research, analysis, prototyping, documentation and workflow automation, while continually identifying new opportunities to increase organizational leverage and self-service.