AI Governance Manager
AI in this role
Manage AI model approval processes, inventories, and governance frameworks to ensure compliance and responsible AI innovation.
Are you excited by the opportunity to help shape scalable AI governance processes that support innovation while maintaining effective risk management?
Do you enjoy working closely with data scientists, technical teams, and stakeholders to create practical governance solutions that deliver clear business value?
About our Team
Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality.
About the Role
As an AI Governance Manager, you will play a key role in operating and enhancing AI governance processes across the organisation. You will partner with data scientists, model owners, and governance stakeholders to support model approvals, inventory management, regulatory compliance, and the continued evolution of a scalable governance framework that enables responsible AI innovation.
Responsibilities
- Own and run day-to-day AI/model approval and review processes, ensuring consistent and timely turnaround.
- Maintain the model inventory as the authoritative record of models in development and production.
- Act as the primary day-to-day point of contact for data scientists and model owners navigating governance requirements.
- Track and report on the health of the model portfolio and the effectiveness of approval processes.
- Manage and continuously improve governance products supporting approvals and inventory management.
- Identify opportunities for automation, self-service capabilities, and process improvement.
- Support the evolution of governance policies, standards, and risk assessment methodologies.
- Maintain audit-ready documentation and support compliance, audit, and risk management activities.
Requirements
- A data science background with hands-on experience building, training, validating, or deploying machine learning models, gained as a data scientist, ML engineer, or in a closely related technical role.
- Experience with, or strong interest in, AI/model governance, model risk management, or a related risk/compliance discipline.
- Strong organizational skills and comfort owning operational processes end-to-end, including maintaining structured records such as a model inventory.
- Practical understanding of relevant AI/data regulation and standards.
- A continuous-improvement mindset.
- Strong communication skills, able to explain governance requirements clearly to technical model owners and translate technical detail for non-technical stakeholders.
- Ability to work independently on operational delivery while contributing constructively to longer-term framework design.
- Prior experience with model inventory, MLOps, or model risk management tooling, and exposure to governance framework or policy development.
Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About the Business
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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How we rate this
AI Governance Manager at RELX rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where ai governance was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where risk management was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: ML Ops, AI Safety, AI Governance, Machine Learning, and Risk Management. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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