Director, R&D Data Enablement/Data Products

Role Summary

Director, R&D Data Enablement/Data Products

Responsibilities

• Define and lead the multi-year strategy for R&D data foundations and data products, aligned with R&D priorities, digital/AI ambitions, and enterprise data strategy.
• Establish and communicate a clear roadmap for delivering cross-domain operational data layers (e.g., studies, sites, patients, compounds, products) and domain-specific data products.
• Drive alignment with business leadership by linking data foundations to measurable outcomes (e.g., trial efficiency, accelerated submissions, improved patient safety).
• Oversee design and implementation of scalable R&D data foundations leveraging medallion/ lakehouse architecture principles.
• Partner with data engineering to build shared “golden / analytics ready” data products and reusable domain-specific data layers.
• Ensure harmonization of external and internal standards (CDISC, HL7/FHIR, MedDRA, internally defined ontologies / standards) embedding FAIR data principles.
• Build a portfolio of high-value data products that address critical R&D use cases (e.g., portfolio insights, clinical trial optimization, regulatory intelligence).
• Establish best practices for data product design, lifecycle management, SLAs, and adoption metrics.
• Partner with business owners to embed data products into decision-making workflows, ensuring measurable impact and user adoption.
• Deliver high-quality, analytics-ready datasets and features that enable AI/ML use cases across the R&D lifecycle.
• Partner with AI/ML and data science teams to accelerate model development by ensuring data foundations are curated, contextualized, and compliant.
• Champion innovation by piloting AI-enabled data products and scaling successful solutions.
• Lead and mentor a multidisciplinary team including Business/Data Analysts, Data Stewards, and Data Modelers to deliver on the data enablement goals.
• Collaborate with domain leaders, governance, and platform teams to ensure seamless integration of data foundations with governance, access, and compliance frameworks.
• Act as a trusted advisor to senior R&D stakeholders, translating scientific and operational needs into scalable data solutions.
• Lead forums and communities of practice to drive a culture of data product thinking and self-service adoption.
• Define and track key metrics for adoption, business impact, and ROI (e.g., reduced cycle times, cost savings, improved decision confidence).
• Establish feedback loops to enhance usability, quality, and scalability of data products.
• Continuously assess emerging technologies and practices to advance the organization’s data enablement maturity.

Qualifications

• Bachelor’s degree in Life Sciences, Data Management, Computer Science, or related field; Master’s or PhD preferred.
• 10+ years of experience in data management, data products, or analytics enablement, with significant experience in Pharma R&D.
• Proven track record of designing and delivering scalable data foundations and products that drive measurable business outcomes.
• Expertise in R&D data domains and lifecycle (Research, Clinical Development, Clinical Operations, Global Statistics & Data Science, Safety, Regulatory, CMC, Portfolio).
• Hands-on experience with modern data platforms and tools (Databricks for data lakehouse/ product development, Informatica for cataloging and quality, Reltio or equivalent for MDM, cloud-native data services).
• Deep understanding of industry data standards (CDISC, HL7/FHIR, MedDRA, etc.) and FAIR principles.
• Strong leadership skills with experience managing cross-functional teams and influencing at executive levels.
• Excellent communication, stakeholder management, and change leadership skills.
• Passion for enabling AI and digital transformation in Pharma R&D through data.

Skills

• Strategy development and roadmapping
• Data architecture and lakehouse design
• Data product development and lifecycle management
• Cross-functional leadership and stakeholder management
• AI/ML data enablement and analytics collaboration
• Governance, compliance, and FAIR data principles

Education

• Bachelor’s degree in Life Sciences, Data Management, Computer Science, or related field; Master’s or PhD preferred.

Additional Requirements

• Travel: Minimal