Director, Product

NBCUniversal•Universal City, CA

7d•$160,000 - $205,000•Hybrid

About The Position

NBCUniversal is seeking a Director of Product to lead Audience Decisioning & Marketing Effectiveness within NBCUniversal Enterprise Product. The role leads products that help marketers identify and engage the right audiences, measure the impact of those decisions, and improve marketing effectiveness. The portfolio includes audience exploration and creation, predictive decisioning, experimentation, measurement, and optimization. The Director owns portfolio strategy, roadmap, and investment priorities, and leads a product team that turns consumer intelligence into scalable marketing capabilities. The role builds and develops a high-performing team with clear ownership, strong product practices, and capabilities suited to the evolving portfolio. The Director works closely with Marketing, Marketing Strategy & Success, Consumer Data, Consumer Identity, Data Science, Engineering, Analytics, and activation teams to create reusable products for NBCUniversal brands and businesses. This position currently follows a hybrid schedule, requiring work from the office at least four days per week. The salary range is $160,000–$205,000 per year, and the role is eligible for a bonus and long-term incentives.

Requirements

Bachelor's degree or equivalent experience.
10+ years of experience in Product Management, Program Management, Marketing Science, Engineering, or Applied Science.
Experience defining product strategy, portfolio roadmaps, and investment priorities.
Demonstrated experience building, managing, and developing high-performing product teams, including hiring, coaching, performance management, career development, and team structure.
Strong understanding of paid and owned marketing workflows, including audience development, targeting, activation, measurement, and optimization.
Experience building products that use customer data, behavioral signals, predictive models, analytics, or machine learning to support business decisions.
Experience with marketing measurement concepts such as experimentation, incrementality, attribution, and statistical uncertainty.
Ability to work cross-functionally and influence without authority.

Nice To Haves

Experience with AI-enabled or conversational products.

Responsibilities

Lead and develop product team members, establish clear ownership, and use marketer feedback, product usage, experimental results, and business outcomes to guide prioritization, adoption, and ongoing improvement.
Define and communicate product vision, portfolio strategy, roadmap, and investment priorities for audience decisioning and marketing effectiveness products.
Lead products across the marketing decision-and-learning lifecycle, including audience exploration and creation, predictive recommendations, measurement, learning, and optimization.
Develop audience and decisioning capabilities that help marketers understand consumers, identify behavioral signals, compare and prioritize audiences, and determine marketing actions, including affinity, propensity, response prediction, and next-best-action capabilities.
Lead marketing effectiveness capabilities, including experimentation, incrementality, promotional effectiveness, audience treatment effects, creative effectiveness, channel effectiveness, and cross-channel learning.
Establish a closed learning loop in which measured outcomes improve future recommendations, models, targeting strategies, campaign design, and product capabilities.
Partner with marketers and Enterprise Product Strategy & Success to understand workflows, business objectives, constraints, and opportunities, and translate needs into scalable product capabilities.
Partner with Consumer Data and Consumer Identity to define reusable behavioral signals, exposure and outcome data, semantic definitions, and identity capabilities needed for decisioning and measurement.
Partner with Governance, Privacy, and Cyber Security teams to ensure compliance.
Work with Data Science, Analytics, Engineering, and Data teams to operationalize predictive models, experimentation, causal measurement, and optimization techniques in scalable and reliable products.
Evaluate and deliver AI and agentic capabilities that simplify marketer workflows, improve decision quality, and make decisioning and measurement capabilities easier to use.