Credit Model Validation Manager (Machine Learning & NPV Models)

Responsibilities

We are representing a rapidly growing financial services organization seeking a Credit Model Validation Manager to join their second line of defense team in Cardiff. This hands-on role focuses on providing independent oversight and validation of credit decisioning models, including machine learning scorecards, origination probability of default models, and net present value frameworks across multiple lending products.

You will lead independent validation activities for models used in credit strategy and decisioning, ensuring they are fit for purpose, appropriately governed, and performing as expected. Your work will include supporting oversight of broader credit risk models such as IFRS9, stress testing, and economic response frameworks. You'll perform statistical analyses to independently assess model performance, developing challenger models where appropriate to test assumptions and strengthen validation conclusions.

Additional responsibilities include:

• Reviewing ongoing model performance monitoring to ensure lending models perform within risk thresholds and supporting first line teams when action is required
• Improving the Model Risk Framework by overseeing policies, standards, and procedures to embed best practice across the business
• Writing clear and impactful model validation reports and presenting findings and actions in relevant committees
• Partnering with credit strategy and modelling teams to support the embedding of the model risk framework and establishing consistent validation standards
• Leading the adoption of AI tools to enhance model validation approaches

What We're Looking For

Our client requires a candidate with strong background and practical experience in credit model development and/or validation, particularly with exposure to machine learning or statistical models used in credit decisioning. Essential experience includes decision science scorecards, origination/underwriting PD models, and NPV/unit economics modelling.

Strong SQL and Python skills are essential for hands-on data work. Experience with data visualization tools such as Tableau or Looker is a plus. You must be data-driven with deep understanding of statistical techniques for credit and model risk.

The ideal candidate will:

• Understand how models are used in real-time decisioning and lending strategies, balancing commercial and risk outcomes
• Possess strong written and verbal communication skills to articulate complex problems and solutions to non-experts
• Have a track record of building and maintaining trusting relationships with stakeholders at all levels while providing effective and respectful challenge
• Be impact-driven and proactive in identifying issues and opportunities to improve outcomes
• Be passionate about technology and innovative financial services

The technology stack includes Google Cloud Platform, dbt, BigQuery SQL, Python for data science and machine learning, Go, and AWS. Prior experience with all these tools is not required.

How We Work With You

When you apply through Get A Job.ai, our talent team will carefully review your application and conduct an initial screening. If your background aligns with our client's requirements, we will submit your profile to them for consideration. The client's interview process typically involves four stages via video call: an initial recruiter conversation, a call with the Senior Model Validation Manager, a role-specific discussion with credit modelling colleagues including a case study, and a behavioural interview.

Please apply exclusively through Get A Job.ai. Do not contact the client organization directly, as this may disqualify your application.

Pay

Compensation details will be discussed during the screening process with our recruiting team.

Equal Employment Opportunity: Get A Job.ai is committed to fostering an inclusive environment. All qualified applicants will receive consideration for employment without regard to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, veteran status, neurodiversity, or disability status.