Group Vice President, Product Management

About the role

The Opportunity As Group VP, Head of Product, you are the accountable executive owner of Wiley’s AI & Data Analytics Business Unit product portfolio—the company’s designated second growth engine.

Key Responsibilities

• Unified Product Strategy & Roadmap: Own an integrated strategy and roadmap across AI & Data Analytics Platform Services, Database Solutions, and Audience Solutions, ensuring the product lines share a common foundation and build on shared capabilities over time.
• Commercial Requirements Translation: Own commercial intake, evaluate priorities against strategy, and convert them into a sequenced roadmap with milestones, business cases, and clear launch/hold decisions.
• Product Architecture: Design the product architecture to serve corporate buyer demand and near-term revenue opportunities.
• Market Validation & Evidence-Based Prioritization: Define leading indicators for execution and partner with data science and commercial teams to validate the content-depth advantage use case by use case, investing where depth is proven.
• Build/Buy/Partner Decisions: Lead the product dimension of the build/buy/partner agenda by defining the commercial framing, strategic rationale, and partner guardrails.
• Global Team Management: Lead and develop a high-performing, multi-disciplinary product organization spanning product management, UX, and product strategy, and build the processes and culture required for software-led, enterprise-grade execution.
• Strategic Collaboration: Partner with the General Manager, commercial leaders, Head of Data Science, and Head of Technology to ensure the product strategy and roadmap realize the division's AI-powered vision.

Requirements

• Enterprise Product Leadership: 15+ years of product management experience, with at least 7 years leading product organizations in enterprise SaaS, data products, or AI/ML platforms.
• Demonstrated track record of owning a product portfolio from early-stage validation through scaled commercial deployment including revenue achievements, including defining pricing architecture, access models, and product economics.
• Commercial Strategy & Positioning: Ability to translate complex technical features into clear, outcome-based value propositions for different buyer personas (e.g., C-Suite vs. End User).
• Experience in designing and iterating SaaS pricing models (usage-based, seat-based, or tiered) to maximize Net Revenue Retention (NRR).
• Data & AI Product Depth: Proven experience building and commercializing data products (structured datasets, APIs, knowledge graphs, AI-powered analytics) for enterprise buyers in regulated markets. You understand provenance, rights governance, and compliance (GDPR, CCPA) as product requirements.
• Corporate R&D Market Experience: Familiarity with corporate R&D buyers in pharma, biotech, engineering, or adjacent verticals — including their procurement cycles, enterprise integration expectations, and the competitive landscape.
• Platform Thinking: Demonstrated ability to run a multi-product portfolio on a shared platform foundation, avoiding one-off solutions that are costly to maintain and don’t create long-term customer or revenue value.
• Commercial Instinct: Strong grasp of product economics (usage-based pricing, tiered subscriptions, API monetization, data licensing, access controls and usage tracking) and ability to tie product decisions to ARR, NRR, and unit economics.
• Interpersonal & Organizational Complexity: Proven ability to lead through shared accountability across commercial, data science, and engineering stakeholders.
• Technical Literacy: Working knowledge of modern data stack technologies, API product design, and enterprise integration architectures.
• Analytics & Experimentation: Proficiency in product analytics, A/B experimentation, and evidence-based prioritization methodologies.
• Enterprise Compliance: Familiarity with enterprise security and privacy standards (SOC2 Type II, ISO 27001, GDPR/CCPA) as product design requirements.