Lead Product Manager

Company Description

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

Job Description

The Opportunity

We are seeking a seasoned and influential Product Lead to drive the strategic evolution of Media Planning and Strategy products. This role requires a unique leader who can equally balance both developing for user workflows and commercializing measurement data.

You will be responsible for defining the future state of media planning and strategy tools, ensuring that the tools not only provide best-in-class user experience but are powered by the most sophisticated, high-quality data and methodologies in the market. This leadership role is a critical link between engineering, data science, and commercial teams, with a mandate to drive efficiency, standardization, and innovation.

What You’ll Do

As the Product Lead, you will own the end-to-end product strategy, execution, and success across a critical area of the media planning and strategy product portfolio:

1. Functionality & User Experience (Platform)

• Workflow Strategy: Define the multi-year product roadmap focusing on scalability, standardization, data delivery and innovation.
• Usability & Adoption: Partner with UX/UI design, engineering teams, and Customer Service to deliver a platform experience that drives high user adoption among media strategists and planners.
• Process Optimization: Lead cross-functional initiatives with Data Operations and Engineering to streamline data pipelines, improve quality assurance, and significantly accelerate the time-to-market for new data sets and methodological updates.
• Data Science Partnership: Work closely with Data Science and Engineering to create and extend data models using new data sources creating actionable, consumable insights within the platform.

2. Leadership & Commercialization

• Executive Alignment: Present the comprehensive product vision to executive leadership and secure resources for strategic initiatives.
• Go-to-Market: Collaborate with Sales and Marketing to define the value proposition, training, and commercial strategy for product launches and feature rollouts.
• Team Development: Mentor and guide other Product Managers and associate staff, ensuring a unified product strategy across the area of ownership.

Qualifications

Critical Skills & Experience

• A bachelor's degree in a quantitative field (e.g., Computer Science, Data Science, Economics) or a related business field.
• 8+ years of progressive Product Management experience, with at least 3 years in a lead or principal role overseeing a complex product line in the B2B or Ad Tech space.
• Dual Expertise: Demonstrated ability to lead both feature/UI development (functionality) and data-as-a-product offerings (data).
• Technical Data Fluency: Strong understanding of data processing, measurement methodologies, statistical modeling, and how to productize complex data science outputs into simple user interfaces.
• Strategic Communication: Proven track record of aligning diverse stakeholders (Engineering, Data Science, Commercial, Executive) around a singular product strategy.

Desired:

• Experience scaling products through standardization/syndication or migrating custom features into core platform offerings.
• Prior experience building or scaling cross-channel media planning, optimization, or attribution tools.
• Background in a B2B SaaS environment where data is the core commercialized asset.
• Experience with ad tech and/or media planning (e.g., audience segmentation, campaign forecasting, programmatic activation, cross-channel measurement).
• Direct experience defining an organizational AI/ML product strategy or working closely with Data Operations to reduce data latency.

Additional Information

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