Principal Credit Risk Analyst

We are seeking a talented Principal Credit Risk Analyst to join our growing Credit Risk Analytics team. This role is specifically designed for professionals with 6-10 years of experience in the lending industry who are looking to develop their career in credit risk analytics and statistical modelling within the banking sector.

Please note: This position is for a Principal Credit Risk Analyst role focused on credit risk assessment and modelling, not financial analysis.

As a Principal Credit Risk Analyst, you will contribute to the development, daily management and enhancement of our credit risk analytics capabilities. This is an excellent opportunity for someone with experience in unsecured lending to get wider exposure and larger remit (affordability strategy, including use of Open Banking and other alternative data sources, underwriting scorecards and credit strategy, pricing models and strategies, low and grow strategies, pre-collection strategies, launch of new credit products) whilst working with cutting‑edge statistical models, data‑driven insights and best‑in‑class datasets.

The role focuses on the UK market and requires experience of the UK lending landscape, but you will have the opportunity to work in a pan‑European team and get exposure to credit risk analytics across our international markets including Germany, Austria, Norway, Spain, Italy, and other European markets.

The role is ideal for a very experienced analyst who wants to stay hands‑on while developing their mentoring/supervising and DS/analytical product management skills.

• Data Analysis & Insights: Opportunity to own end‑to‑end strategies for specific population segments. Collect, analyse, and interpret data from multiple sources including internal systems, open banking and Credit Reference Agencies (CRAs) to identify trends, patterns, and opportunities that inform credit policy, credit limit and pricing strategies.
• Model Development: Developing and maintaining statistical models, including scorecards, ML models and other credit risk assessment tools.
• Stakeholder
  
  Collaboration:
  
  Provide clear, actionable insights and recommendations to stakeholders across the business, supporting informed decision‑making and business growth.
• Cross‑functional Teamwork: Work collaboratively with colleagues in the decision sciences and analytics team, as well as other departments across different locations.
• Communication & Reporting: Present complex analytical findings to both technical and non‑technical audiences through clear presentations, reports, and data visualisations.
• Mentoring: Mentor and supervise junior analysts on model and strategy development projects, and Python model pipeline development.

• Bachelor degree in Mathematics, Statistics, Economics, Physics, Computer Science, Engineering, or related quantitative discipline from a well‑regarded university.
• 6-10 years of experience in analytics, data analysis, or lending/credit assessment within the financial services sector.
• Previous experience working for an unsecured lender, preferably on Credit card products (bank, building society, fintech, or similar credit provider).

• Strong analytical and problem‑solving abilities with excellent attention to detail.
• Proficiency in SQL for data extraction, manipulation, and analysis.
• Strong programming experience in Python (ideally for model development).
• Understanding of statistical analysis techniques and data modelling methodologies.
• Experience in predictive modelling (logistic regression and GBM knowledge at minima).
• Understanding of machine learning techniques applied to credit risk.

• Excellent written and verbal communication skills in English.
• Ability to translate complex data into clear, actionable business insights.
• Strong presentation skills with experience communicating to diverse audiences.
• Proven ability to work effectively in fast‑paced environments whilst managing multiple priorities.
• Team player.

• Postgraduate qualification in a relevant quantitative field.
• Knowledge of credit risk regulations and best practices in the UK…