At a Glance
- Tasks: Lead data strategy and AI initiatives to transform MedTech Surgery with innovative solutions.
- Company: Join a pioneering MedTech company focused on improving healthcare through data and AI.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career development.
- Why this job: Make a real impact in healthcare by leveraging data and AI to enhance surgical outcomes.
- Qualifications: Master's or PhD in relevant fields with 10+ years in data leadership roles.
The predicted salary is between 100000 - 150000 £ per year.
The Global Technology Leader will serve as the business-facing leader accountable for the data strategy, analytics outcomes, and AI enablement across MedTech 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 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.
- 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 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 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.
- Platform & Architecture Partnership (Modern Data Stack): Define target-state data architecture for Surgery 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. Support pathways that interface with clinical environments 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 high-performing teams across data engineering, analytics, and applied AI; develop talent pipelines and role clarity. Create a culture of product thinking, operational excellence, and continuous improvement; implement modern ways of working with strong portfolio governance.
- Financial & Vendor/Partner Management: Own budget planning, 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.
Qualifications & Experience
- Master's 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.
- Strong leadership skills, with the ability to inspire and manage multidisciplinary teams.
- Exceptional communication and stakeholder management abilities, with experience collaborating across global organizations.
Core Competencies
- Strategic Vision & Execution
- Technical Leadership in AI & Analytics
- Change Management & Innovation
- Regulatory Acumen
- Collaboration & Influence
Required Skills
- Business Architecture
- Business Process Design
- Business Savvy
- Computer Programming
- Emerging Technologies
- Human-Computer Interaction (HCI)
- Leadership
- Organizational Change Management
- Platform as a Service (PaaS)
- Product Knowledge
- Program Management
- Software Development Management
- Strategic Change
- Tactical Planning
- Technical Credibility
Preferred Skills
- Business Architecture
- Business Process Design
- Business Savvy
- Computer Programming
- Emerging Technologies
- Human-Computer Interaction (HCI)
- Leadership
- Organizational Change Management
- Platform as a Service (PaaS)
- Product Knowledge
- Program Management
- Software Development Management
- Strategic Change
- Tactical Planning
- Technical Credibility
Director, MedTech Surgery Data Analytics & AI employer: 6010-Biosense Webster Inc. Legal Entity
As a leader in MedTech Surgery Data Analytics & AI, our company fosters a dynamic work culture that prioritises innovation and collaboration. We offer exceptional employee growth opportunities through mentorship and continuous learning, alongside competitive benefits that support work-life balance. Located in a vibrant area, we provide a unique environment where cutting-edge technology meets meaningful impact, empowering our team to drive transformative change in healthcare.
Contact Details:
6010-Biosense Webster Inc. Legal Entity Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Director, MedTech Surgery Data Analytics & AI
✨Tip Number 1
Network like a pro! Reach out to connections in the MedTech and data analytics space. Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those related to AI and data analytics. This will give potential employers a tangible sense of what you can bring to the table, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by diving deep into the company’s data strategy and recent projects. Tailor your responses to highlight how your experience aligns with their goals, especially in areas like data governance and AI enablement. This shows you're not just interested in any job, but specifically in theirs.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search. So, get that application in and let’s make it happen!
We think you need these skills to ace Director, MedTech Surgery Data Analytics & AI
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in data strategy and AI, especially in MedTech. We want to see how your skills align with our goals, so don’t hold back on showcasing relevant projects!
Showcase Your Leadership Skills:As a Director, you'll need to inspire and manage teams. Share examples of how you've led multidisciplinary teams in the past, particularly in data analytics or AI. We love seeing candidates who can demonstrate strong leadership and collaboration.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to describe your achievements and how they relate to the role. We appreciate clarity and directness, so avoid jargon where possible!
Apply Through Our Website:We encourage you to submit your application through our website for the best chance of being noticed. It’s the easiest way for us to track your application and ensure it gets into the right hands!
How to prepare for a job interview at 6010-Biosense Webster Inc. Legal Entity
✨Know Your Data Strategy
Before the interview, dive deep into the company's data strategy and how it aligns with MedTech Surgery. Be ready to discuss specific examples of how you've co-created or executed a data strategy in your previous roles, especially focusing on measurable outcomes and OKRs.
✨Showcase Your AI Expertise
Prepare to talk about your experience with AI enablement and model lifecycle management. Highlight any successful AI/ML projects you've led, particularly those that moved from pilot to scale, and be ready to discuss the challenges you faced and how you overcame them.
✨Demonstrate Governance Knowledge
Familiarise yourself with data governance principles and compliance standards relevant to the MedTech industry. Be prepared to discuss how you've built or operationalised governance models in the past, ensuring privacy and security controls were in place.
✨Engage with Stakeholder Management
Think about your approach to stakeholder engagement and how you've facilitated collaboration across different teams. Be ready to share examples of how you've managed multidisciplinary teams and ensured alignment between business needs and data capabilities.
