Job Function:

Job Sub Function:

Job Category:

All Job Posting Locations:

Job Description:

The Global Technology Leader 6 Director, MedTech Surgery Data & Analytics and AIwill serve as the business-facing leader accountable for the data strategy, analytics outcomes, and AI enablement across MedTech Surgery 6turning data into trusted, compliant, and scalable products that improve decision-making, performance, and innovation across R&D-adjacent, commercial, supply chain, service, and digital surgery domains.

This role will build and lead a team spanning data engineering, analytics, data product management, and applied AI/ML/GenAI and will partner deeply with business and functional stakeholders to ensure business intimacy and measurable value realization.

1) Strategy & Outcomes (Business Value)

• Co-create and execute a multi-year Data & AI strategy and roadmap for MedTech Surgery aligned to business priorities and transformation milestones; translate strategy into measurable outcomes and OKRs.
• Identify and prioritize high-impact use cases across Surgery domains (e.g., commercial growth, demand sensing, intelligent service, computer vision for quality, workflow automation), balancing near-term wins and scalable platforms.
• Establish value tracking (benefits, adoption, quality, cycle-time) and regularly communicate progress to senior stakeholders.

2) Data as a Product (Trusted, Standardized, AI-Ready)

• Position data as a strategic, reusable asset by creating and scaling data products for priority datasets with clear ownership, lineage, and quality controls 6enabling trusted, connected, AI-ready insights
• Drive standardization for priority datasets (examples referenced in current OKR language include: UDI, Product, Regulatory, Product Config, Clinical) and enable secure access through approved marketplace patterns.
• Implement stewardship and operating cadences that strengthen data literacy and adoption across the Surgery organization.

3) Data Governance, Risk, and Compliance-by-Design

• Build and operationalize an enterprise-grade governance model for Surgery data and AI (policies, controls, decision forums, stewardship), aligned to a federated model and consistent data management practices.
• Ensure privacy-by-design and security-by-design controls across data pipelines, analytics products, and AI solutions.
• Establish audit-ready processes for critical workflows (access controls, traceability, and monitoring) and partner with Cybersecurity, Regulatory Affairs, Legal, and Quality functions.

4) AI Enablement & Model Lifecycle (From Pilot to Scale)

• Lead the end-to-end lifecycle for applied AI/ML/GenAI solutions: use case intake, feasibility, data readiness, model development, validation, deployment, monitoring, and lifecycle governance.
• Enable scalable AI creation and deployment patterns aligned to Surgery platforms and labs, including capabilities such as data ingestion, enrichment/annotation, cohorting/access, model creation, deployment, and commercialization into clinical workflows where applicable.
• Champion responsible AI practices: transparency, human oversight, bias/risk assessment, and ongoing performance monitoring (informed by common industry 3Responsible AI 4 leader role patterns).

5) Platform & Architecture Partnership (Modern Data Stack)

• Define target-state data architecture for Surgery (integration patterns, pipeline standards, interoperability, observability) and drive reusable components/patterns to accelerate delivery of data products.
• Partner with platform/architecture leaders to ensure scalable cloud foundations, APIs, and data platforms that can support analytics and AI workloads.
• Where relevant to digital surgery, support pathways that interface with clinical environments (e.g., interoperability and integration patterns) as already referenced in existing digital-first strategy language.

6) Operating Model & Stakeholder Leadership (BU-Driven, Enterprise-Connected)

• Establish a clear engagement model between BU-driven data science/engineering needs and central capabilities; ensure decision rights and resource allocation enable speed while maintaining standards.
• Serve as the primary point of accountability for Surgery Data & AI across Regions and Functions, enabling cross-region leverage without losing business specificity.
• Represent Surgery in cross-enterprise councils/communities aligned to data standards, governance, and AI capability building.

7) People Leadership & Capability Building

• Build, mentor, and lead high-performing teams across data engineering, analytics, and applied AI; develop talent pipelines and role clarity (including upskilling and strategic hiring).
• Create a culture of product thinking, operational excellence, and continuous improvement; implement modern ways of working (agile/product delivery) with strong portfolio governance.

8) Financial & Vendor/Partner Management

• Own budget planning (where applicable), vendor strategy, and partner ecosystem decisions for data/analytics tooling, AI services, and delivery capacity.
• Ensure cost discipline and scalable, reusable delivery models.

Success Measures

• Increased adoption and satisfaction for priority data products; measurable improvements in data quality/availability for top datasets.
• AI use cases moved from pilot to scaled deployment with clear value realization and controlled lifecycle monitoring.
• Governance maturity improvements: clearer ownership, lineage, and audit-ready controls for critical workflows.
• Improved speed-to-insight and execution across Surgery value streams enabled by interoperable data platforms and trusted analytics.

• Master 27s or PhD in Data Science, Computer Science, Engineering, or a related field; advanced business training (MBA or equivalent) is highly desirable.
• 10+ years of experience in data & analytics leadership roles, with a proven track record in AI strategy and implementation, preferably within MedTech, healthcare, or life sciences.
• Demonstrated expertise in data governance, cloud analytics platforms, machine learning, and regulatory compliance (GDPR, HIPAA, MDR).
• Strong leadership skills, with the ability to inspire and manage multidisciplinary teams.
• Exceptional communication and stakeholder management abilities, with experience collaborating across global organisations.

• Strategic Vision & Execution
• Technical Leadership in AI & Analytics
• Change Management & Innovation
• Regulatory Acumen
• Collaboration & Influence

Required Skills:

Preferred Skills:

The anticipated base pay range for this position is :