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Credit risk analyst

St James
Aimee Willow Connex Ltd
Credit risk analyst
£50,000 - £85,000 a year
Posted: 22h ago
Offer description

Credit Risk Modelling Analyst

London Office- Hybrid working

The Role

We’re looking for a Credit Risk Analyst to take ownership of how we understand, measure, and forecast customer defaults across our lending portfolio.

Key Accountabilities

* Maintain and enhance the firm’s default and delinquency monitoring

* Analyse how customers transition through risk states, identifying trends and drivers of early-stage arrears and defaults

* Develop, maintain, and interpret performance curves (e.g. vintages, cohort analyses, Month on Book curves) to understand changes in credit quality

* Produce clear, concise insight for senior stakeholders, turning complex analysis into actionable recommendations

* Support the development and refinement of credit strategies, including acquisition policy changes and behavioural risk management

* Work closely with data, product, and risk teams to shape how the business measures performance and exposure

* Assist in the design of portfolio health dashboards and risk MI, ensuring reliable and timely reporting

* Drive improvements in data quality, reporting consistency, and how the business records and interprets customer lifecycle events

Skills & Experience

* Proven experience in a credit, portfolio, or risk analytics role

* Strong understanding of consumer or commercial credit lifecycle, including arrears, roll rates, charge-off processes, and recoveries

* Hands-on analytical skills with the ability to work confidently with large datasets

* Proficiency in SQL for deep-dive investigations and building repeatable analysis

* Confidence with visualisation tools (e.g. Power BI / Tableau)

* Comfortable working with performance curves and diagnosing shifts in default behaviour

* Skilled in presenting complex findings to stakeholders, including non-technical audiences

* Strong commercial awareness - understanding how default timing affects profitability, exposure, and model outcomes

* Experience with statistical modelling is beneficial but not essential

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