Director,MedTech Surgery Data Analytics & AI Job High Wycombe area,England UK,IT/Tech

The Global Technology Leader – Director, Med Tech Surgery Data & Analytics and AI will serve as the business-facing leader accountable for the data strategy, analytics outcomes, and AI enablement across Med Tech Surgery—turning 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.

Key Responsibilities

Strategy & Outcomes (Business Value):
Co-create and execute a multi-year Data & AI strategy and roadmap for Med Tech 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.

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—enabling 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.

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.

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 Responsible AI leader role patterns).

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.

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.

People Leadership & Capability Building:
Build, mentor, and lead…

Director, MedTech Surgery Data Analytics & AI