Digital RnD Decision Fabric Product Owner

Role Summary

Digital RnD Decision Fabric Product Owner – Morristown, NJ. Lead the design and implementation of the R&D Decision Fabric, an AI-driven decision infrastructure that unifies data, analytics, AI models, and decision-making workflows across R&D to enable data-driven, scalable decision support and accelerate medicine development.

Responsibilities

• Lead the decision fabric’s technical design and implementation, collaborating with the architecture, Digital Data and AI, and digital R&D Data Product and Platform teams
• Define the range of capabilities of the R&D Decision Fabric agents and their interfaces with the data and analytics fabrics to support all R&D decision support use cases
• Define best practices and guidelines for digital R&D to build decision fabric elements or full agentic workflows focusing on connectivity, reusability, configurability, accessibility, security, governance, etc.
• Maintain an inventory of all agents to avoid agentic chaos
• Lead cross-R&D governance to prioritize use cases for the Decision Fabric and focus on synergies and reuse

Qualifications

• Required: 8+ years’ experience in digital product management, preferably in the Pharmaceutical Industry
• Required: Proven expertise in designing and implementing Agentic AI workflows, preferably supporting enterprise decision-making
• Required: Experience in data integration, data management, data mastering and platform supporting those
• Required: Experience or familiarity with the following (selection):
  • GenAI / Agents: Experience building GenAI-based applications or agents beyond PoC/PoV
  • DevOps & MLOps: CI/CD pipelines and ML model deployment/monitoring to support agile development of decision capabilities
  • Cloud Platforms: Familiarity with major cloud services (AWS preferred)
  • Data Infrastructure: Data lakes, warehouses, and pipelines (Snowflake, Databricks, Azure Synapse)
  • API Architecture: API design and management tools for seamless integration
  • AI/ML Frameworks: Various ML types (deep learning, regression, optimization, reinforcement learning, NLP) and their cloud implementations
  • Governance & Compliance Tools: Systems for audit trails, version control, regulatory compliance
  • Decision Management Systems: Rules engines, business process management, and decision modeling standards
• Required: Excellent communication, stakeholder engagement, and problem-solving skills
• Required: Experience leading cross-functional teams and ideation workshops
• Required: Ability to translate business needs into digital solutions that drive value
• Education: Bachelors degree required, Master’s degree preferred

Skills

• Strategic product leadership for AI-driven decision platforms
• Stakeholder management and cross-functional collaboration
• Requirements gathering, roadmapping, and backlog prioritization
• Strong problem-solving and analytical thinking

Education

• Bachelors degree required
• Master’s degree preferred