Director of Data & AI

McLaren Automotive is a British manufacturer of luxury supercars and hypercars that grew out of the legendary Formula 1 racing team. It creates high-performance road cars.

• Own McLaren's data, analytics and AI strategy, platforms, and delivery teams
• Build and run an enterprise data platform, analytics estate, and AI platform for business teams, supported by a central capability
• Lead the data engineering, data analytics, AI/ML, and data collaboration teams; integrate generative AI into engineering, design, quality, and customer-facing products; and establish governance across data and AI
• Define principles and a multi-year roadmap for platforms, people, products, and governance; secure executive sponsorship; and translate the roadmap into quarterly objectives and funding plans
• Provide a secure, reliable, self-service platform with clear service levels, documented standard patterns, and reusable components, connected to enterprise systems
• Provide a secure, multi-model AI platform that keeps McLaren data within approved boundaries, and lead generative AI integration into design, engineering, quality, and customer-facing products
• Prioritise the data and AI product portfolio, from ingestion and models to semantic layers, dashboards, and AI agents; establish clear business cases; and ensure shipped products are accurate, version-controlled, and monitored in production
• Establish and lead the data and AI governance forum; define data ownership, quality standards, lifecycle, and master data management; and enforce AI usage policy, model evaluation, and data residency requirements
• Embed privacy by design, data classification, and lineage; prevent unmanaged use of consumer AI tools; reduce intellectual property and cyber risk; and work with cyber security and cloud teams on controls
• Collaborate with product development and engineering, manufacturing and operations, and commercial and customer experience teams; align with cloud and security roadmaps; agree ownership of integration points with peer directors; and represent data, analytics, and AI in technical design forums
• Own platform operating and capital budgets, manage unit costs, hold suppliers accountable, and reduce reliance on contractors by building permanent in-house capability

• Understand engineering, design, manufacturing, quality, and commercial domains, and how data and AI create advantages in them
• Have experience with multi-model architectures, retrieval, agents, MLOps, and integration into engineering and manufacturing environments
• Have experience leading data engineering and analytics teams, building pipelines and lakehouse architectures, semantic models, and business intelligence products used across a large organisation
• Have experience with data and AI governance, privacy by design, classification, and lineage
• Have extensive leadership experience in data and AI, ideally in engineering or technology
• Have experience building, mentoring, and retaining specialist teams, and setting shared standards and ways of working
• Have experience managing platform budgets, controlling unit costs, and demonstrating the value of technology investments
• Have a track record of building academic and industry research partnerships

• 25 Days’ holiday, plus bank holiday; annual buy and sell of up to five days
• Enhanced company pension scheme
• Discretionary annual bonus award
• Private medical insurance and health cash plan
• Life assurance benefit
• Ability to apply for a sabbatical of up to one year after two years’ service
• Lifestyle benefits, including discounted shopping
• Generous parental leave policies
• Wellbeing initiatives, employee assistance programme, and free financial and mortgage advice