Staff Product Manager, tvScientific

Pinterest
San Francisco, CA, US; Remote, USPosted 4 March 2026

Job Description

<div class="content-intro"><p><strong>About Pinterest:</strong></p> <p>Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.</p> <p>Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the <a href="https://www.pinterestcareers.com/our-life/pinflex/">flexibility</a> to do your best work. Creating a career you love? It’s Possible.</p></div><p><strong>About tvScientific</strong></p> <p>tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.<br><br></p> <p>We are seeking a Staff Product Manager to lead the strategy and execution for identity graph and data partnership initiatives, critical to enabling high-performance, privacy-compliant targeting across our CTV advertising platform. This role will focus on developing and refining identity resolution capabilities, managing graph-based data integrations, and expanding the reach and accuracy of our audience recognition and measurement infrastructure.<br><br></p> <p>Success in this role will require a blend of deep technical expertise in identity data, graph modeling, and data architecture, as well as strong product instincts and cross-functional leadership skills. You will work closely with Engineering, Data Science, and external data partners to build a resilient and scalable identity foundation for precise audience targeting and measurement.<br><br></p> <p><strong>What you'll do:</strong></p> <ul> <li>Own the identity product strategy at tvScientific <ul> <li>Lead the product vision for tvScientific’s identity graph, enabling persistent, multi-device recognition across CTV and digital channels.</li> <li>tvSci Identity will service multiple teams throughout the product and engineering ecosystem, it will be your role to align with leadership of those teams to gather requirements, define goals and monitor success.</li> <li>Partner with Data Engineering and Data Science to architect and optimize graph-based data models that represent user identity, household relationships, and device linkages.</li> <li>Design APIs and services for real-time identity resolution, enrichment, and activation in programmatic ad workflows.</li> </ul> </li> <li>Grow identity data partnerships <ul> <li>Source, evaluate, and onboard third-party identity and behavioral data providers to enhance graph completeness and targeting capabilities.</li> <li>Work with Legal, Security, and Data teams to ensure all data partnerships comply with CCPA, GDPR, and other global privacy standards.</li> <li>Lead the technical integration and operationalization of new identity and graph enrichment partners, ensuring reliable ingestion, mapping, and deployment.</li> <li>Maintain an ongoing view of the identity and data ecosystem, and recommend partnership or build strategies accordingly.</li> </ul> </li> <li>Deliver world-class adtech product <ul> <li>Write detailed product requirements, data specifications, and user stories for identity graph services and data integration projects.</li> <li>Coordinate with Engineering and Infrastructure teams to deliver performant graph storage, traversal, and querying systems.</li> <li>Support Sales, Marketing, and Customer Success with technical narratives ... (truncated, view full listing at source)