Group Vice President, Product Management

Head of Product (Data Analytics & AI)

Group Vice President, Head of Product – accountable executive owner of Wiley’s AI & Data Analytics Business Unit product portfolio, the company’s designated second growth engine.

Your mission is to turn strategy into a proven roadmap that scales across three connected product lines: AI & Data Analytics Platform Services (including the Applied Research Intelligence Platform), Database Solutions (transforming proprietary reference works into machine‑readable data products), and Audience Solutions (evolving advertising into an AI‑powered marketing intelligence product). The three lines share a common platform foundation; you ensure each reinforces the others.

You report to the Chief AI & Data Analytics Officer and lead product managers & UX across all lines.

• Unified Product Strategy & Roadmap
  :
  Own an integrated strategy and roadmap across all product lines, ensuring shared capabilities grow over time.
• Commercial Requirements Translation
  :
  Own commercial intake, evaluate priorities, and convert them into a sequenced roadmap with milestones, business cases, and clear launch/hold decisions.
• Product Architecture
  :
  Design architecture to serve corporate buyer demand and near‑term revenue opportunities, defining the sequence of Applied Research Intelligence Platform capabilities.
• Productization of Proprietary Collections
  :
  Lead transformation of legacy content into structured, machine‑readable, high‑margin data products and develop a vision for advertising & audience engagement using behavioral analytics.
• Market Validation & Evidence‑Based Prioritization
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  Define leading indicators and partner with data science & commercial teams to validate content‑depth advantage use cases.
• Build/Buy/Partner Decisions
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  Lead product dimension of the build/buy/partner agenda with commercial framing, strategic rationale, and partner guardrails.
• Global Team Management
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  Develop a high‑performing, multi‑disciplinary product organization spanning product management, UX, and product strategy, and build the required processes and culture for software‑led, enterprise‑grade execution.
• Strategic Collaboration
  :
  Partner with the General Manager, commercial leaders, Head of Data Science, and Head of Technology to realize the division’s AI‑powered vision.

• Enterprise Product Leadership
  : 15+ years of product management with at least 7 years leading product organizations in enterprise SaaS, data products, or AI/ML platforms; track record of portfolio ownership from validation to scaled deployment, including pricing architecture and product economics.
• Commercial Strategy & Positioning
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  Translate complex technical features into outcome‑based value propositions for diverse buyer personas, maintain competitive market awareness, and design SaaS pricing models to maximize Net Revenue Retention.
• Data & AI Product Depth
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  Proven experience building and commercializing data products (structured datasets, APIs, knowledge graphs, AI‑powered analytics) for regulated enterprise buyers, with knowledge of provenance, rights governance, and compliance (GDPR, CCPA).
• Corporate R&D Market Experience
  :
  Familiarity with corporate R&D buyers in pharma, biotech, engineering, or adjacent verticals, including procurement cycles and enterprise integration expectations.
• Platform Thinking
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  Ability to run a multi‑product portfolio on a shared platform foundation, avoiding costly one‑off solutions.
• Commercial Instinct
  :
  Strong grasp of product economics (usage‑based pricing, tiered subscriptions, API monetization, data licensing) and ability to tie 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
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  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…