Model Governance Director, Data Science

Are you passionate about building and owning practical, scalable AI governance frameworks that enable innovation while managing risk?

About the Role

As Model Governance Director, Data Science, you will own and evolve the end-to-end AI and model governance framework on behalf of the Data Science function. You will provide strategic leadership, helping to ensure AI systems are developed and deployed responsibly while balancing regulatory compliance, risk management, innovation, and business outcomes. This role partners closely with technical, legal and product stakeholders to embed effective governance into how we use AI.

Responsibilities

• Own the end-to-end AI and model governance framework on behalf of the Data Science function, including policy implementation and continuous improvement.
• Define standards for model risk classification, approvals, documentation, monitoring, and lifecycle management.
• Set the strategic roadmap for AI governance tools and processes.
• Ensure compliance with relevant AI regulations and standards, including the EU AI Act, GDPR, and emerging global requirements.
• Partner with Legal, Compliance, Privacy, and Information Security teams to maintain governance policies.
• Act as a key contact for audits, regulators, customers, and industry forums on AI governance matters.
• Establish governance metrics, reporting, model inventory oversight, and operational effectiveness measures.
• Lead and develop governance capability while supporting training and awareness across the organisation.

• Significant experience in AI/model governance, model risk management, data governance, compliance, or a related risk discipline, including people management.
• Strong knowledge of AI governance regulations and frameworks (EU AI Act, ISO 42001 or similar) and their practical application.
• Experience designing and operating governance processes for AI/ML models in production environments.
• Strong commercial judgment with the ability to balance innovation, risk, and business objectives.
• First class stakeholder management and communication skills, with experience influencing senior technical and business leaders.
• Proven track record of creating scalable governance processes, driving continuous improvement, and introducing automation.
• Working knowledge of the AI/ML lifecycle, including data sourcing, model development, validation, deployment, and monitoring.