Credit Risk Analyst
8 days ago
Tonbridge
Credit Risk Analyst Competitive and Dependent on Experience Tonbridge, Kent Office based for training then hybrid 2–3 days per week in the office Our client is a growing specialist lender undergoing an exciting period of transformation, modernising its data infrastructure and credit risk capabilities. This newly created role offers the opportunity to play a key part in shaping how credit data is managed. The role will act as a bridge between the Credit function and the wider data strategy, working closely with a newly appointed Head of Data. The role combines credit portfolio management, regulatory compliance, and advanced data analysis to ensure robust risk management and operational efficiency. Responsibilities include: • Maintain and validate loan portfolio data, ensuring accuracy, integrity, and robust reconciliation processes, • Analyse credit and portfolio data to identify trends, anomalies, and early warning risk indicators, • Support stress testing and impairment analysis, including understanding IFRS9 provisioning impacts, • Build and enhance reporting and analytical tools using advanced Excel, SQL, and Python, • Review property valuations and populate/maintain credit databases to support informed lending decisions, • Support model validation, data modelling, and continuous process improvement initiatives The successful candidate will possess: • Experience within credit risk and analysis in the commercial or residential property lending sector., • Advanced Excel skills with the ability to build and maintain structured data models and databases, • Working knowledge of SQL and an interest in developing Python skills (commercial experience not essential), • Understanding of IFRS9 and stress testing concepts, • Experience analysing loan application and portfolio data, with the ability to identify risk flags and data anomalies Why Apply? This is an opportunity to join a stable and purpose-driven lender at a pivotal stage of its evolution. You will benefit from: • Exposure to senior stakeholders and strategic decision-making, • The opportunity to influence how credit data is structured and utilised, • Autonomy and ownership within a growing function, • Investment in modern tools and technical development