AI Governance Manager

Overview

In this role, you will lead and evolve AI governance processes within Data Science to enable responsible AI innovation while managing risk. You will partner with model owners and governance stakeholders to drive model approvals, inventory management, and regulatory compliance at scale. The position focuses on turning governance into an efficient, auditable, and self-improving operation that supports cutting-edge AI work. You will influence policy and tooling to balance speed with risk controls, in a data-driven, cross-functional environment.

Pay / Benefits

• wellbeing initiatives
• shared parental leave
• study assistance
• sabbaticals

Responsibilities

• Own and run day-to-day AI/model approval and review processes with timely turnaround
• Maintain the model inventory as the authoritative record of models in development and production
• Serve as primary point of contact for AI software requesters, data scientists, and model owners navigating governance requirements
• Track and report on health of the model portfolio, 3rd party AI software, and effectiveness of approvals
• Manage and improve governance products supporting approvals and inventory management
• Identify opportunities for automation, self-service capabilities, and process improvement
• Support evolution of governance policies, standards, and risk assessment methodologies
• Maintain audit-ready documentation to support compliance, audit, and risk management activities

Key requirements

• Data science background with hands-on ML experience (training, validating, deploying)
• Interest or experience in AI/model governance, model risk management, or related compliance discipline
• Strong organizational skills with end-to-end operational ownership and structured records
• Practical understanding of relevant AI/data regulation and standards
• Continuous-improvement mindset
• Strong communication skills to explain governance to technical owners and translate to non-technical stakeholders
• Ability to work independently on operational delivery while contributing to long-term framework design
• Experience with model inventory, MLOps, or model risk management tooling; exposure to governance framework or policy development

• strong communication
• ability to translate technical details for non-technical stakeholders
• independence and initiative
• model inventory
• MLOps
• governance tooling

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