Credit Model Validation Manager (Machine Learning & NPV Models)

Overview

This role supports the growth of the organization’s Borrowing (lending) business by providing independent oversight and challenge to credit model development teams. As part of the Credit Model Validation team (second line of defence), you will validate and oversee a suite of credit models to help ensure models are fit for purpose, appropriately governed, explainable, and performing as expected.

The role has a particular focus on models used for customer-level decisioning and credit strategy, including underwriting scorecards, origination PD models, and Net Present Value (NPV) / unit economics models, across lending products.

Responsibilities

• Lead hands-on independent validation of credit decisioning models used in Borrowing strategies, including machine learning, decision science, and NPV models.
• Support oversight and validation of broader credit risk models, including IFRS9, stress testing, and economic response models.
• Build deep understanding of the organization’s credit models and use that knowledge to provide impactful input and challenge to model developers to improve modelling capabilities.
• Review ongoing model performance monitoring to ensure lending models perform within risk thresholds; support first line of defence teams when action is required.
• Perform statistical analyses to independently assess model performance, including developing challenger models where appropriate to test assumptions and strengthen validation conclusions.
• Improve the Model Risk Framework by overseeing policies, standards, and procedures to embed best practice, including alignment with up-to-date regulatory guidelines.
• Write clear, impactful model validation reports and present findings and actions in relevant committees.
• Partner with first line of defence credit strategy and modelling teams and wider risk teams to help embed the model risk framework and establish consistent validation standards.
• Embrace new and innovative technology, including leading adoption of AI tools to enhance the model validation approach.

Requirements

• Strong background and practical experience in credit model development and/or validation.
• Exposure to machine learning or statistical models used in credit decisioning, including decision science scorecards, origination/underwriting PD models, and NPV / unit economics modelling.
• Data-driven with strong analytical skills and deep understanding of statistical techniques for credit and model risk.
• Strong SQL and Python skills, with hands-on ability to work with data.
• Practical experience in either model validation or model development within a financial services environment, including practical experience using Python to develop, validate, or analyze machine learning and statistical models.
• Strong written and verbal communication skills, with ability to explain complex problems and priorities clearly for non-experts.
• Ability to build and maintain trusting stakeholder relationships and provide effective, respectful challenge.
• Understanding of how models are used in real-time decisioning and lending strategies, including balancing commercial and risk outcomes.

Preferred Qualifications

• In-depth knowledge of credit decisioning models.
• Experience with data visualisation tools such as Tableau, Looker, or similar.

Compensation & Benefits

• Salary: £79,000 - £93,000
• Incentive Awards tied to performance
• Flexible working hours
• £1,000 learning budget each year for books, training courses, and conferences
• Work-from-home support; MacBooks provided for employees, with extra support for fully remote workers’ home setup

Location

• London or Remote (UK)
• Distributed working within the UK is supported, with ad hoc meetings in London.