VP, Data & AI Products

Why Hearst Magazines?

Hearst Magazines is one of the largest publishers in the world, with more than 30 brands, including Cosmopolitan, ELLE, Esquire, Good Housekeeping, Harper’s BAZAAR, Women’s Health, Men’s Health, Seventeen and Oprah Daily. We reach more than 150 million people every month in the United States alone.

But we’re more than just our magazines. We engage our audience across all mediums and channels—print, digital, video, and social—with sophisticated content creation, distribution, and data capabilities. We create, package, and sell products with cutting‑edge technology and proprietary platforms.

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.

• 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.

• 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 stakeholders.
• Experience working in a large‑scale media, publishing, or digital content organization is highly desirable.
• Demonstrated ability to collaborate effectively with cross‑functional teams (engineering, data science, design, marketing, sales, editorial).
• Excellent…