Director of Data & AI

Overview

In this role you will own McLaren’s data, analytics and AI strategy and run the enterprise data and AI platforms. You will lead data engineering, analytics, AI/ML and data collaboration teams, embedding governance and privacy by design while enabling self-service for business units. You’ll drive multi-year roadmaps, secure sponsorship, and integrate generative AI into design, engineering and customer-facing products. This is a chance to shape a scalable data/AI-enabled future for a high-performance brand.

Pay / Benefits

• Structured career development framework
• 25 days’ holiday plus bank holidays
• Enhanced pension scheme
• Discretionary annual bonus
• Private medical insurance and health cash plan
• Life assurance benefit

Responsibilities

• Define the multi-year platform, people, product and governance roadmap and translate it into quarterly objectives and funding
• Deliver a secure, reliable, self-service data/AI platform with clear SLAs, reusable components and integration to enterprise systems
• Lead the integration of a multi-model AI platform and generative AI into design, engineering, quality and customer-facing products
• Prioritize data and AI product portfolio with clear business cases and ensure production artifacts are version-controlled and monitored
• Establish and chair data and AI governance forum; define data ownership, quality, lifecycle and master data management; enforce AI usage policy and data residency
• Embed privacy by design, data classification and lineage; collaborate with cyber security and cloud teams on controls
• Collaborate with product development, engineering, manufacturing, operations, commercial and customer experience teams; align with cloud and security roadmaps; clarify ownership of integration points
• Own platform operating and capital budgets, manage unit costs, and reduce reliance on contractors by building in-house capability to scale

Key requirements

• Understanding of engineering, design, manufacturing, quality and commercial domains and how data/AI creates value
• Experience with multi-model architectures, retrieval, agents, MLOps, and integration into manufacturing environments
• Leadership of data engineering and analytics teams; building pipelines, lakehouse architectures and BI products
• Data/AI governance including usage policy, model evaluation and data residency; privacy-by-design
• Proven track record in leading specialist teams and setting standards across an organization
• Budget management for platforms; ability to demonstrate value of technology investments
• Experience building academic and industry research partnerships
• Ability to articulate long-term direction while delivering day-to-day, multi-platform pragmatism
• Ability to foster demand for data/AI from peer directors and establish early ownership of integration points
• Fluency across data engineering, analytics and generative AI; ability to earn trust of engineers and executives
• Champions federated, automated governance and mitigates uncontrolled AI usage
• Experience growing teams and communities and driving real adoption across business units

• Leadership and people development
• Cross-functional collaboration
• Strategic thinking and pragmatism
• Multi-model architectures
• MLOps
• Lakehouse and semantic models

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