Global Director, Clinical Data & AI Strategy

Smith+Nephew; Andover (MA); On-site; USD 165,250 - 236,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) retirement plan

Tuition reimbursement

Paid time off

Parental leave

Hybrid work model

Wellness programs

Job summary

Smith+Nephew is seeking a Director of Clinical Data & AI to set the global strategy for data platforms, AI enablement, and evidence-generation across clinical programs. You will own the clinical data lifecycle, from acquisition to analytics, and drive an enterprise data architecture that scales across geographies and regulatory regimes.

Responsibilities include defining unified operating models, overseeing data governance, and leading cross-functional teams in data science, statistics, and

Qualifications

• Minimum 10 years experience across clinical data, AI/ML, and data platforms
• Proven leadership of multi-domain teams (data management, engineering, data science, AI, programming)
• Demonstrated ownership of enterprise data architecture (e.g., data lake/platform)
• Experience supporting regulatory submissions and clinical evidence generation

Responsibilities

• Define and lead the global Clinical Data & AI strategy
• Own design, governance, and evolution of CDL and data models
• Oversee data pipelines, integration, and interoperability frameworks
• Drive AI/ML capabilities across the clinical lifecycle
• Ensure compliance with regulatory standards (FDA, GDPR, HIPAA)
• Lead collaboration across data science, statistics, and programming teams

Skills

Clinical data platforms

AI/ML leadership

Regulatory submissions

Enterprise data architecture

Data governance

Education

BA degree required

Advanced degree in Data Science/Biostatistics/CS

Tools

Databricks

Job description

Smith+Nephew is seeking a Director of Clinical Data & AI to set the global strategy for data platforms, AI enablement, and evidence-generation across clinical programs. You will own the clinical data lifecycle, from acquisition to analytics, and drive an enterprise data architecture that scales across geographies and regulatory regimes.

Responsibilities include defining unified operating models, overseeing data governance, and leading cross-functional teams in data science, statistics, and