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Credit Risk Modeller (Contractor)
Tesco Mobile – Business Integrity
Location – Manchester 2 days a week
Duration – 6 months
Role Overview
Tesco Mobile is undertaking a significant transformation of its credit risk capability, including the implementation of a new credit decisioning platform, enhanced data services, and refreshed customer lifecycle strategies. As part of this programme, we are developing a suite of new credit risk models covering application risk, behavioural (in-life) risk, Probability of Default (PD), exposure risk, and proposition-level risk.
We are seeking an experienced Credit Risk Modeller with strong hands-on expertise in scorecard development, bureau data modelling, and regulatory-aligned model design. This is a key delivery role responsible for developing high-quality models that meet governance standards and are ready for deployment into our new credit decisioning platform.
This is a hands-on contractor opportunity, ideal for someone who can quickly integrate into the team, take ownership of model development, and deliver high-quality outputs at pace.
Key Responsibilities
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Develop new credit risk models, including:
- Application scorecards
- Behavioural (in-life) scorecards
- Probability of Default (PD) models
- Exposure risk models
- Proposition-level risk models
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Extract, cleanse, manipulate and prepare large datasets using Python and SQL to support model development, validation and deployment.
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Build and optimise predictive models using TransUnion and Equifax bureau data, ensuring appropriate variable selection, mapping and regulatory compliance.
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Perform model validation activities including:
- Back-testing
- Population stability analysis
- Characteristic stability analysis
- Reject inference
- Performance monitoring
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Produce clear, comprehensive and audit-ready model documentation, technical specifications and governance artefacts.
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Support model implementation, user acceptance testing and production deployment.
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Contribute to the ongoing development of model monitoring frameworks and model governance processes.
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Share modelling best practice and provide technical guidance to colleagues to help build capability across the wider Credit Risk team.
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Essential Skills & Experience
Technical Skills
- Strong Python programming skills with extensive experience in:
- Feature engineering
- Statistical modelling
- Predictive analytics
- Model development
- Advanced SQL skills with experience extracting and transforming large, complex datasets.
- Proven experience developing and implementing:
- Application scorecards
- Behavioural (in-life) models
- Probability of Default (PD) models
- Exposure risk models
- Proposition-level credit risk models
Credit Risk Expertise
- Extensive hands-on experience in retail credit risk modelling.
- Strong understanding of credit bureau data, particularly:
- TransUnion
- Equifax
- Experience selecting, interpreting and engineering bureau variables for predictive modelling.
- Knowledge of model performance monitoring, calibration and ongoing model optimisation.
Governance & Regulatory Knowledge
- Good understanding of credit risk model governance.
- Experience producing documentation suitable for model governance and audit.
- Knowledge of regulatory expectations relating to:
- Model governance
- Fairness and bias
- Explainability
- Probability of Default (PD) modelling
- Regulatory model standards
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Personal Attributes
- Self-starter who can work independently with minimal supervision.
- Able to quickly understand complex data environments and business requirements.
- Strong analytical and problem-solving skills.
- Excellent attention to detail and commitment to producing high-quality work.
- Effective communicator, able to explain technical concepts to both technical and non-technical stakeholders.
- Comfortable working in a fast-paced transformation programme with changing priorities.
To Apply
Please apply with an up-to-date CV. Candidates will ideally show evidence of the above in their CV in order to be considered.
Please be advised if you haven't heard from us within 48 hours then unfortunately your application has not been successful on this occasion, we may however keep your details on file for any suitable future vacancies and contact you accordingly.
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