Director, Clinical Data & AI

Life Unlimited. At Smith+Neb we design and manufacture technology that takes the limits off living. The Director of Clinical Data & AI is the global functional leader responsible for the strategy, architecture, and operational execution of clinical data and AI capabilities supporting end-to-end evidence generation. This role owns the clinical data lifecycle—from data acquisition and management to advanced analytics, AI enablement, and synthetic/simulated data—ensuring all data assets are high-quality, interoperable, and fit-for-purpose for regulatory, scientific, and operational decision-making.

The Director serves as the enterprise authority on clinical data platforms and AI-enabled evidence generation, driving integration across clinical systems, data engineering, AI/ML, and statistical/clinical programming. This position has full accountability for the strategy, execution, quality, and evolution of the Clinical Data & AI function globally.

• Global Clinical Data & AI Strategy
• Define and execute the global strategy for Clinical Data & AI aligned to enterprise evidence-generation and AI transformation goals
• Establish a unified operating model integrating:
  • Clinical systems (EDC, eCOA, registries)
  • Clinical Data Lake & central data model
  • Data management and data engineering
  • AI/ML and advanced analytics
• Serve as the enterprise authority on clinical data architecture and AI enablement for clinical & medical affairs across all BUs and geographies
• Partner with Clinical Study Management, Clinical Strategy, Regulatory, Medical Affairs, Statistics, and IT to define data-driven evidence strategies
• Clinical Data Architecture & Platforms
• Own the design, governance, and evolution of:
  • Clinical Data Lake (CDL) and standardized data models
  • Clinical systems ecosystem (EDC, eCOA, registry ingestion, integrations)
  • Data pipelines, transformation, and interoperability frameworks
• Ensure scalable, compliant, and extensible architecture supporting:
  • Cross-study analytics
  • Real-world data integration
  • Device + clinical data linkage
• Drive standardization (e.g., CDISC-based models) and elimination of data silos
• AI, Data Science & Advanced Analytics
• Lead development and deployment of AI/ML capabilities across the clinical lifecycle, including:
  • Data quality automation and monitoring
  • AI-assisted clinical study reporting and analytics
  • Cross-study insights and meta-analyses
• Drive integration of AI into core workflows, not point solutions
• Establish best practices for:
  • Model development, validation, monitoring
  • Responsible AI (traceability, reproducibility, regulatory alignment)
• Oversee collaboration between data science, statistics, and programming teams
• Synthetic Data, Simulation & Virtual Twins
• Own strategy and execution for:
  • Synthetic clinical data generation
  • Simulation frameworks for study design and operational planning
  • Virtual twin development for patient- and study-level modeling
• Ensure alignment with regulatory expectations for transparency and scientific validity
• Integrate synthetic and simulated data into:
  • Study design optimization
  • Evidence generation (e.g., hybrid designs, external controls)
• Clinical Data Management & Quality
• Oversee global clinical data management function, ensuring:
  • High-quality, consistent, and inspection-ready data
  • Efficient study startup (eCRF design, database builds) and closeout
  • Risk-based monitoring and analytics-driven data review
• Embed AI, machine learning modeling, and automation into CDM workflows to improve efficiency and quality
• Ensure alignment with regulatory and compliance standards (FDA, EU MDR, GDPR, HIPAA)
• Statistical & Clinical Programming Integration
• Own alignment and integration of:
  • Statistical programming (TFLs, ADaM outputs)
  • Clinical programming (data pipelines, transformations)
• Ensure seamless data flow from raw data → analysis-ready datasets → reporting
• Drive standardization, automation, and reuse across studies and programs
• Leverage AI solutions to accelerate programming across Global Clinical and Medical Affairs
• Operational Excellence & Delivery Model
• Own intake, prioritization, and delivery across:
  • Data platform initiatives
  • AI/ML programs
  • Study-level data operations
• Implement scalable delivery models for…