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Senior Credit Risk Modelling Analyst

Job in Maple Cross, Hertfordshire, WD3, England, UK
Listing for: Renault Group
Full Time position
Listed on 2026-06-01
Job specializations:
  • Finance & Banking
    Data Scientist, Financial Advisor / Consultant
Salary/Wage Range or Industry Benchmark: 60000 - 80000 GBP Yearly GBP 60000.00 80000.00 YEAR
Job Description & How to Apply Below
Location: Maple Cross

Responsibilities

  • 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 model performance and implement controls to prevent data quality issues affecting the models.
  • Participate in the constant improvement of models, propose new potential segments to target, comply with regulatory evolution, and create or improve documentation as necessary.
  • Work closely with external auditors (experience with external audit is essential).
  • Stay updated on industry trends, regulatory changes, and best practices in credit risk modelling to keep company policies current and effective.
  • Prepare high‑quality, detailed model documentation, implementation reports, and performance monitoring presentations for senior management, internal audit, and regulatory bodies.
  • Assess compliance of implemented models with EBA (European Banking Authority) and PRA (Prudential Regulation Authority).
Knowledge and Skills
  • Strong academic background with a degree in a quantitative discipline such as Statistics, Mathematics, Economics, Physics, or Engineering.
  • Detailed understanding of underlying statistical theory is essential.
  • Significant experience in proactively problem solving and analysing large, complex data sets, identifying trends and making data‑driven decisions.
  • Advanced and demonstrable programming skills in SAS are mandatory.
  • Proficiency in at least one additional statistical programming language such as Python or R.
  • Ability to work under pressure and with short deadlines.
  • Advanced knowledge of 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, able to articulate complex technical concepts to non‑specialist audiences, both orally and in written form.
Equal Employment Opportunity

The company is committed to creating an inclusive working environment and ensuring equal employment opportunities regardless of race, colour, ancestry, religion, gender, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, and other protected characteristics.

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Position Requirements
10+ Years work experience
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