Lead the vision, strategy, governance, and development of the Clinical Data Layer, enabling secure and efficient clinical data flow across the development lifecycle.
Lead the vision, strategy, governance, and development of the Clinical Data Layer, ensuring secure and efficient data flow from source systems to trusted data products across the clinical development lifecycle.
Compensation
This position's reasonably anticipated salary range is $148,000-$195,000 annually. The actual salary offered will consider internal equity and may also vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience, among other factors.
Responsibilities
Own the vision, strategy, governance, adoption, and continued development of the Clinical Data Layer
Define and communicate long-term vision, roadmap, investment case, and business strategy
Establish governance for data products, metadata, reference data, quality controls, access, stewardship, and measures of platform value
Partner with architecture and technology teams to enable scalable integration, common data models, interoperability, and reusable clinical data flows
Shape safe, high-value uses of artificial intelligence, intelligent automation, semantic models, knowledge graphs, and agent-based capabilities
Requirements
Bachelor’s degree in data science, computer science, clinical informatics, life sciences, technology, statistics, or a related field
Nice to have: led large-scale business transformation involving clinical data, digital capabilities, and global, cross-functional stakeholders in regulated environments
Nice to have: understanding of clinical data standards, metadata management, data architecture, statistical analysis workflows, governance, and the clinical development lifecycle
Nice to have: familiarity with cloud data platforms, data lakes, data products, application programming interfaces, and modern integration patterns
Nice to have: ability to connect business and technical perspectives and understand artificial intelligence, machine learning, agents, semantic layers, and modern data ecosystems
