VP, Data & AI Products

Overview (

Why This Role?

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The VP, Data & AI Products will own and drive the product strategy for leveraging data, analytics, and artificial intelligence across all Hearst Magazines digital properties. This pivotal leadership role is responsible for ensuring our products are intelligent and personalized, deliver uniquely valuable user experiences, provide actionable insights to internal teams (such as editorial, marketing, and advertising), and unlock new pathways for revenue and sustainable business growth.

You will build and lead a team of specialized product leaders to champion a data-first and AI-enabled product culture across the organization.

Hearst Magazines’ portfolio of more than 30 iconic brands in the U.S— including Cosmopolitan, ELLE, Esquire, Good Housekeeping, Harper’s BAZAAR, and Popular Mechanics— inspires, entertains, and builds new and bold experiences for an engaged and growing audience across digital, video, social and print, reaching nearly 130 million readers and site visitors each month. With sophisticated content creation, cutting-edge technology, and industry-leading data capabilities, we make media and products that move people across all platforms.

We are a global media company that publishes nearly 200 magazine editions and 175 websites around the world—and together, we are shaping what’s next.

• Develop and champion a clear, compelling product vision and strategy for data and AI initiatives, aligned with Hearst Magazines' overall business objectives and product mission.
• Own and manage the product roadmaps for enterprise-wide data and AI product initiatives, including personalization engines, recommendation systems, audience intelligence platforms, AI-powered content/operational tools, and the "product view" of the underlying data platform.
• Lead, mentor, and grow a high-performing team of Product Leads focused on specific domains within data and AI (Personalization & Recommendation, AI-Powered Content & Operational Tools, Audience Intelligence & Data Products, Data Platform Product Strategy & Enablement).
• Collaborate closely with senior leadership across Product, Engineering (including Data Engineering and Data Science teams), Design, Editorial, Commercial, and Brand GMs to identify opportunities, define product requirements, and ensure successful execution and adoption of data/AI products.
• Drive the strategy for how data is ethically collected, processed, transformed, and made accessible for product innovation, ensuring user privacy and compliance.
• Champion the development of data literacy and AI understanding within the broader product management organization and across Hearst Magazines.
• Define and monitor key success metrics for data and AI products, ensuring they deliver measurable impact on user engagement, operational efficiency, and revenue.
• Stay at the forefront of advancements in data science, machine learning, AI, and their applications in the media industry, translating these into actionable product strategies.
• Explore and define product strategies for new data and AI-driven monetization opportunities, in partnership with commercial teams.
• Foster a culture of innovation, experimentation, and continuous improvement within the Data & AI Products team and its collaborations.
• This is a hybrid position based in New York City, with an in-office requirement of four days per week.

• 12+ years of experience in product management, with at least 7+ years specifically focused on data products, analytics platforms, machine learning, or AI-powered products.
• Proven track record of successfully defining, launching, and scaling data-intensive and AI-driven products that deliver significant user and business value.
• 5+ years of experience in a leadership role, managing and mentoring product managers.
• Deep understanding of the data and AI lifecycle, including data collection, processing, model development, deployment, and iteration.
• Strong strategic thinking and ability to translate complex technical concepts into clear product strategies and value propositions for non-technical…