Manager, Technology Product Management, AI Data Insights

Johnson & Johnson Johnson & Johnson · Pharma · Titusville, NJ +1

Johnson & Johnson is seeking a Manager, Technology Product Management, AI Data Insights to lead product strategy, roadmap, execution, and delivery of Data, Analytics, and AI products. The role involves identifying and implementing AI use cases, driving the development and scaling of AI, Generative AI, AI Agents, and intelligent automation, and championing responsible AI practices. The candidate will lead Agile product teams and foster innovation.

What you'd actually do

  1. Lead a portfolio of Commercial Operations products and platforms, accountable for strategy, objectives and key results, value realization, and business value.
  2. Develop and drive data, analytics capabilities that strengthen reporting, forecasting, decision support and operational efficiency.
  3. Align product investments, roadmaps, and technology capabilities with organizational priorities, customer needs, and enterprise strategy.
  4. Managed product backlog, delivery, technical execution, and stakeholder alignment across business, technology, and vendor teams.
  5. Lead Agile product teams and cross-functional partnerships.

Skills

Required

  • technology product management
  • analytics
  • digital transformation
  • healthcare, life sciences, or a regulated industry
  • cloud technologies such as AWS
  • analytics platforms such as Power BI and Tableau
  • Agile product management methodologies
  • predictive analytics and forecasting
  • modern ML/LLM architectures and their real-world applications
  • retrieval-augmented generation (RAG)
  • prompt engineering
  • AI agents
  • semantic and context layers
  • Machine Learning
  • AI tools (e.g., Claude Code, Copilot Studio)
  • cross-functional partnerships
  • stakeholder management
  • influence
  • excellent communication

Nice to have

  • healthcare/life sciences
  • sales performance and execution metrics reporting
  • syndicated data sets
  • performance & execution metrics
  • forecasting applications
  • pharma commercial sales Ops processes
  • roster management
  • territory and hierarch management
  • Incentive compensation reporting
  • commercial functions
  • CRM/Salesforce Life Sciences Cloud
  • AI-enabled product strategy

What the JD emphasized

  • AI use cases
  • AI, Generative AI, AI Agents
  • responsible AI practices
  • healthcare, life sciences, or a regulated industry
  • predictive analytics and forecasting
  • modern ML/LLM architectures
  • retrieval-augmented generation (RAG)
  • prompt engineering
  • AI agents
  • semantic and context layers
  • Machine Learning
  • AI tools (e.g., Claude Code, Copilot Studio)
  • measurable gains in delivery speed, output quality, or personal productivity
  • AI-enabled product strategy

Other signals

  • AI use cases
  • AI, Generative AI, AI Agents
  • responsible AI practices