Roles: AI/ML Lifecycle Management

Responsible for defining GenAI validation requirements and authoring GenAI sub-system validation SOPs. Ensures compliance of GenAI validation activities with regulatory requirements and organizational standards.

Responsible for transforming, aggregating, and integrating data for AI modelling purposes. Designs, supports, and maintains data infrastructure and pipelines. Ensures data quality and accessibility. Role may be performed by the Data Scientist.

Ultimately responsible for owning and supporting the entire AI lifecycle from business understanding through data acquisition, processing, model design, development, evaluation, and monitoring. Accountable for SAT test preparation and execution.

Responsible for AI model deployment, integration with the overarching system, managing incidents related to performance and expected behaviour, and building or implementing monitoring tools for continuous model monitoring and infrastructure support.

Independent statistical subject matter expert (e.g., non-clinical biostatistics team or data scientist with statistical background) who endorses, documents, and approves alternative statistical techniques when standard sampling plans are infeasible or when GenAI performance tests fail. Consulted for