Job Description

Job Purpose

The Senior Credit Risk Modelling Analyst is responsible for building, monitoring, and calibrating the statistical models that underpin the risk assessment framework. This includes application scorecards, Probability of Default (PD), Loss Given Default (LGD), behavioural scorecards, models for stress testing and statistical forward-looking projections.

Your key contributions will be to assist in the local construction of new models, ensure the robust calibration of parameters for the UK portfolio, conduct rigorous back-testing, and provide ongoing monitoring and effective challenge to all models in use. This role also involves building new suite of models for Residual Value risk and Stress testing models for ICAAP. Where models are centralised, you will be required to engage with the Group modelling team and support their model developments as required.

Description

• • Support the end-to-end development and implementation of credit risk models (PD, LGD, EAD)
  • Support the back testing for IFRS9 (PD, LGD, EAD, SICR) and  statistical forward-looking Models.
  • Support  Parameter Estimates for IFRS9 to ensure that the models are running as expected.
  • Monitor the performance of the models and implement controls that help to prevent data quality issues affecting the models.
  • Participate to the constant improvement of the models, propose new potential segment to target, comply with the evolution of the regulation and create or improve the documentation where necessary.
  • Experience with External Audit is essential.
  • Stay updated on industry trends, regulatory changes, and best practices in credit risk modelling to ensure the company's policies remain current and effective.
  • Prepare high-quality, detailed model documentation, implementation reports, and performance monitoring presentations for a range of audiences, including senior management, internal audit, and regulatory bodies.
  • Assess the compliance of the models implemented with both EBA (European Banking Authority) and PRA (Prudential Regulation Authority).

Knowledge & Skills

• • Strong academic background with a degree in a quantitative discipline such as Statistics, Mathematics, Economics, Physics, or Engineering. Detailed understanding of the underlying statistical theory is essential.
  • Significant experience in proactively problem solving and analysing of large, complex data sets, identify trends, and make data-driven decisions.
  • Advanced and demonstrable programming skills in SAS are mandatory for this role.
  • Proficiency in at least one other statistical programming language, such as Python or R.
  • Ability to work under pressure and with short deadlines.
  • Advanced knowledge with machine learning techniques (e.g., Gradient Boosting, Random Forests, deep Neural Networks) and their application in a credit risk context is desirable.
  • Strong communication skills, with the ability to articulate complex technical concepts to non-specialist audiences, both orally and in written form.

This is a hybrid role (2 days a week in the office).

Benefits include:

• 27 days annual leave 
• Private Healthcare - Self + Partner Cover
• Annual bonus scheme - up to 10% non-contractual bonus
• COP Car Scheme (£37.50 per month) - Available to order within the first month
• Loan Plan Scheme - entitled up to 2 vehicles at any one time
• Employee pension contribution of 3.5%/Employer pension contribution of 7.22%
• Flexible Benefit Scheme