Model Governance Manager (Data Science)

Description

The role is about running and improving the AI governance processes used in the Data Science group, keeping innovation moving while managing risk well.

The company combines research information, large data sets and analytics to serve researchers, healthcare professionals and clinical practice.

You will work with data scientists, model owners and governance stakeholders on model approvals, inventory management, regulatory compliance, and a governance framework that can scale to support responsible AI work.

Responsibilities

• Run day-to-day AI and model approval and review, keeping turnaround consistent and on time.
• Keep the inventory of third-party software and models as the single trusted record of models in development and in production.
• Serve as the main day-to-day contact for people requesting AI software and for data scientists and model owners working through governance requirements.
• Report on the health of the model portfolio, the third-party AI software, and how well the approval process works.
• Manage and keep improving the governance tools that support approvals and inventory.
• Find chances to automate work, add self-service options, and improve processes.
• Help develop governance policies, standards, and risk assessment methods.
• Keep documentation ready for audit and support compliance, audit, and risk activities.

Requirements

• A data science background with hands-on work building, training, validating, or deploying machine learning models, as a data scientist, ML engineer, or in a closely related technical role.
• Experience with AI or model governance, model risk management, or a related risk or compliance field, or a strong interest in it.
• Strong organisational skills and the ability to own operational processes end to end, including keeping structured records such as a model inventory.
• A working understanding of relevant AI and data regulation and standards.
• A mindset focused on continuous improvement.
• Strong communication skills: you can explain governance requirements clearly to technical model owners and turn technical detail into terms non-technical stakeholders understand.
• You can run operational delivery independently while helping shape the longer-term framework.
• Prior experience with model inventory, MLOps, or model risk management tools, and exposure to governance framework or policy development.

Conditions

The company supports a healthy work and life balance and offers wellbeing programmes, shared parental leave, study assistance, and sabbaticals.

Country-specific benefits are available based on your location.

Accommodation is available during the hiring process on request.

Applicants should be alert to recruitment scams: the company never asks for money or banking details.

Benefits

• Wellbeing programmes, shared parental leave, study assistance, and sabbaticals.
• Country-specific benefits based on your location.