Head of Data & AI

The Head of Data & AI leads HOYA's enterprise-wide data and artificial intelligence agenda for Group Digital. The role is accountable for establishing the strategy, governance, capabilities and operating model required to turn data and AI into a trusted source of business value across HOYA's divisions.

This is a senior leadership role that combines business transformation, data leadership, AI enablement and responsible governance. The role will shape HOYA's data and AI roadmap, build the foundations for scalable analytics and AI adoption, and ensure that innovation is delivered within clear guardrails for security, privacy, compliance, quality and ethical use.

Success requires the ability to operate at executive level while remaining close enough to the work to drive practical outcomes. The Head of Data & AI must be able to build trust with divisional leaders, translate business priorities into data and AI initiatives, develop internal capability, and lead a pragmatic portfolio of use cases that demonstrate measurable value.

Data & AI Strategy and Leadership

• Define the enterprise agenda — develop and maintain HOYA's data and AI strategy, roadmap and priorities aligned to business outcomes, digital transformation and Group Digital objectives
• Lead the operating model — establish the governance, roles, forums, funding approach and decision rights required to scale data and AI consistently across divisions
• Build executive alignment — engage senior stakeholders across divisions to prioritise high-value opportunities and create shared ownership for adoption and benefits realisation
• Shape the portfolio — maintain a balanced portfolio of data, analytics, automation and AI initiatives, prioritised by business value, readiness, risk and scalability

Data Foundations, Governance and Platforms

• Establish trusted data foundations — drive the development of scalable data platforms, data products, integration patterns and semantic models that enable reliable analytics and AI
• Lead data governance — define standards for ownership, stewardship, data quality, metadata, lineage, classification, retention and access management
• Improve data usability — make priority Group-wide data assets discoverable, understandable and reusable for reporting, analytics, automation and AI use cases
• Partner with infrastructure, architecture and security — ensure data and AI platforms are secure, compliant, resilient and aligned to enterprise architecture principles

AI Enablement, CoE and Responsible Innovation

• Build the AI capability model — define how AI use cases are identified, assessed, built, governed, deployed and supported across HOYA
• Lead responsible AI practices — establish practical guardrails for ethical use, privacy, security, transparency, human oversight and risk management
• Develop the AI Centre of Excellence — shape reusable standards, patterns, tools, review mechanisms and communities that help divisions adopt AI safely and consistently.
• Champion AI adoption — promote practical use of generative AI, Agentic AI and other approved AI capabilities in everyday business workflows

Business Value Delivery and Adoption

• Prioritise value-led use cases — work with divisions to identify high-impact opportunities where data, analytics, automation or AI can improve productivity, decision-making, quality or customer outcomes
• Drive benefits realisation — define success measures, track adoption and outcomes, and ensure initiatives move beyond pilots into sustainable business impact
• Enable change at scale — partner with Communications, HR / L&D and divisional champions to build data literacy, AI literacy and confidence across the organisation
• Manage partner contribution — work with strategic vendors and implementation partners to access expertise, accelerate delivery and ensure knowledge transfer to internal teams

Essential:

• Senior leadership experience in data, analytics, AI, digital transformation or enterprise technology within a multinational or multi-division organisation.
• Proven ability to define and execute a data and AI strategy aligned to business outcomes, governance requirements and technology capabilities.
• Strong understanding of enterprise data platforms, analytics, data governance, data quality, metadata, reporting and AI enablement concepts.
• Working knowledge of generative AI, Microsoft 365 Copilot, AI governance, AI risk management and responsible AI practices.
• Demonstrated ability to influence senior stakeholders, build cross-functional alignment and translate complex topics into clear business decisions.
• Experience leading teams, partners or communities of practice across business and technology domains