AI Governance Director, Data Science

Overview

In this role you will own and evolve the end-to-end AI governance framework for the Data Science function, balancing risk, compliance and innovation. You will collaborate with Legal, Compliance, Privacy and Security to embed governance into AI usage across the organization. You will define risk classifications, approvals, documentation and lifecycle management, and lead the strategic roadmap for governance tools. This role offers influence over audits, regulators and industry forums, driving measurable governance outcomes. You will shape a scalable, data-driven governance program that supports responsible AI at Elsevier.

Pay / Benefits

• wellbeing initiatives
• shared parental leave
• study assistance
• sabbaticals
• competitive compensation
• location flexibility

Responsibilities

• Own and continuously improve the AI and model governance framework for the Data Science function
• Define standards for model risk classification, approvals, documentation, monitoring and lifecycle management
• Set roadmap for AI governance tools and processes
• Ensure compliance with AI regulations and standards (EU AI Act, GDPR, etc.)
• Partner with Legal, Compliance, Privacy and Information Security to maintain governance policies
• Act as primary contact for audits, regulators, customers and industry forums on AI governance
• Establish governance metrics, model inventory oversight and operational effectiveness measures
• Lead and develop governance capability and provide training across the organization

Key requirements

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

• Stakeholder management
• Strategic influence
• Communication
• AI/ML governance and risk management
• Regulatory compliance knowledge (EU AI Act, GDPR)
• Model lifecycle management and monitoring

…