Director of Data & AI

Описание

This role involves owning McLaren's data, analytics, and AI strategy, along with the platforms and teams that deliver it. The Director will build and run a single enterprise data platform, analytics estate, and AI platform for business teams, supported by a central capability.

Responsibilities

• Define the principles and multi-year roadmap covering platform, people, products and governance, secure executive sponsorship, and translate it 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 so teams can deliver faster at a controlled cost
• Provide a secure, multi-model AI platform that keeps McLaren data within approved boundaries, and lead the integration of generative AI into design, engineering, quality and customer-facing products
• Prioritise the portfolio of data and AI products, from ingestion and models to semantic layers, dashboards and AI agents, each with a clear business case, and make sure what the teams ship is accurate, version controlled and monitored in production
• Set up 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 and reduce intellectual property and cyber risk; and work with the cyber security and cloud teams on controls
• Work closely with product development and engineering, manufacturing and operations, and commercial and customer experience teams, and align with the cloud and security roadmaps; agree clear ownership of integration points with peer directors and represent data, analytics and AI in technical design forums
• Own the platform operating and capital budgets, manage unit costs such as cost per pipeline, per report and per AI query, hold suppliers to account, and reduce reliance on contractors by building permanent in-house capability

Requirements

• Understanding engineering, design, manufacturing, quality and commercial domains, and how data and AI create advantage within them
• Multi-model architectures, retrieval, agents, MLOps, and integration into engineering and manufacturing environments
• Leading data engineering and analytics teams, building pipelines and lakehouse architectures, semantic models and business intelligence products used across a large organisation
• Data and AI governance (usage policy, model evaluation, data residency), privacy-by-design, classification and lineage
• Experience in data, AI with extensive in leadership, ideally in Engineering or Technology space
• Building, mentoring and retaining specialist teams, and setting the standards and ways of working they share across the business
• Managing platform budgets, controlling unit costs and demonstrating the value returned from technology investment
• Track record of building academic and industry research partnerships

We offer

• Structured career development framework
• 25 days’ holiday, plus bank holiday. Annual buy & sell 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 only two years’ service
• Benefits you can adapt to your lifestyle, such as discounted shopping
• Generous parental leave policies
• A range of wellbeing initiatives, such as employee assistance programme and free financial & mortgage advice