Director, R&D AI, Insights & Analytics

Position Summary

The Director, R&D AI, Insights & Analytics will lead the strategy and execution of data, analytics, artificial intelligence, and insights capabilities across the R&D organization. This highly visible leadership role will drive the transformation of how data is leveraged throughout the drug development lifecycle, enabling faster clinical trial execution, stronger data governance, more informed decision-making, and scalable AI-driven innovation.

Primary Responsibilities

• Define and execute the R&D insights, analytics, AI, and data capability roadmap aligned with R&D priorities and enterprise data and AI strategies
• Lead the R&D data governance framework, including data ownership, stewardship, ontology, metadata, lineage, business glossary, data quality standards, FAIR data principles, and enterprise-wide semantic consistency
• Establish consistent definitions, metrics, semantic standards, and data quality expectations across R&D to improve trust, reuse, and comparability of information
• Partner with Enterprise IT and data engineering teams to define business requirements and support the design and implementation of modern R&D data platforms, including data lake, lakehouse, and cloud-based solutions
• Provide R&D leadership and subject matter expertise for architecture, platform, technology, and vendor evaluations, ensuring scalability, security, interoperability, and business alignment
• Build and operationalize clinical development benchmarking capabilities, including study start-up, patient enrollment, site performance, cycle times, data quality, and other key development metrics
• Develop dashboards, predictive analytics, and decision-support capabilities that improve patient enrollment, site selection, trial execution, portfolio oversight, and clinical development performance
• Identify, prioritize, and implement opportunities to accelerate clinical trials and R&D processes through AI, machine learning, predictive analytics, intelligent automation, and AI-enabled solutions
• Partner with Enterprise AI and Enterprise IT teams to translate R&D use cases into scalable products, define business requirements and success metrics, and support deployment, adoption, and value realization
• Lead current-state assessments, process mapping, capability mapping, gap analyses, and future-state roadmap development to support R&D transformation and operating model improvements
• Collaborate across Clinical Development, Clinical Operations, Research, Translational Medicine, Data Management, Biostatistics, Regulatory Affairs, Safety, and other R&D functions to identify high-value data and analytics opportunities
• Manage external partners, contractors, and vendors to deliver analytics, governance, benchmarking, and transformation initiatives within approved budgets
• Present strategies, recommendations, progress, risks, and business outcomes to senior leadership, governance forums, and key stakeholders
• Monitor emerging data, analytics, AI, and life sciences technologies and drive innovation and experimentation initiatives that create measurable value across R&D
• Other duties as assigned

Education/Experience/Skills

• Bachelor’s degree in Data Science, Computer Science, Engineering, Life Sciences, or a related field required; advanced degree preferred
• 10+ years of progressively responsible experience in R&D analytics, data strategy, clinical development analytics, AI-enabled solutions, digital transformation, or related disciplines
• Experience within the pharmaceutical, biotechnology, or life sciences industry
• Strong knowledge of the drug development lifecycle and R&D functions, including Clinical Development, Clinical Operations, Research, Translational Medicine, Data Management, Biostatistics, Regulatory Affairs, and Safety
• Experience establishing and leading data governance programs, including data ownership, stewardship, ontology, metadata, lineage, business glossary, data quality standards, and FAIR data practices
• Experience defining or supporting data lake, lakehouse, data fabric, or cloud data strategies and partnering with architecture and engineering teams on platform selection and implementation
• Working knowledge of Databricks, Snowflake, Microsoft Fabric, AWS, Azure, semantic layer technologies, and enterprise metadata or catalog tools
• Experience developing clinical performance metrics, external benchmarking programs, operational dashboards, and analytics supporting patient enrollment, site performance, trial acceleration, and portfolio decision-making
• Experience applying AI/ML, predictive analytics, intelligent automation, or AI-enabled products to solve R&D business challenges
• Experience conducting process mapping, capability assessments, gap analyses, and future-state roadmap development
• Ability to translate business requirements into scalable data, analytics, platform, and technology solutions
• Experience managing cross-functional initiatives, vendors, external partners, and project resources
• Familiarity with regulated R&D environments and clinical data standards, including GxP, CDISC, SDTM, ADaM, and FHIR
• Ability and willingness to travel domestically and internationally as needed