Risk Analyst in London - CER FINANCIAL LTD

Risk Analyst

West End

Hybrid (4 days in the office / 1 WFH)

Permanent

£50,000 - £60,000

cer Financial are working alongside an exciting, international bank who are based in the City of London. They are seeking a Risk Analyst to work with them on a permanent basis.

In this role you will be a quantitative expert in Risk Analytics, developing and maintaining predictive models for credit, market, and liquidity risk to safeguard the bank’s capital.

The responsibilities of the Risk Analyst will include:

• Support the Risk Analytics team (and Risk generally) in delivering and developing insights on a wide range of risks, in particular Credit (including ECL), LGD and PD parameter development.
• Support ICAAP (financial and credit RWA / ECL stress forecasting) and Recovery Planning.
• Development and implementation of scenario analysis and stress testing models generally.
• Support development and assessment of Operational and Climate Risk stress monitoring.
• Run and enhance risk appetite measurement models and related forecasting.
• Contribute to the enhancement of risk data quality.
• Support development of good model governance, including structured development, documentation of models and design and running of model validation tests.

The successful candidate will have:

• University degree (2.1+) with 2–3 years’ post-grad/commercial experience.
• Experience in banking/finance (Risk, Portfolio Analysis, Finance), including credit/liquidity regulatory calculations and reporting.
• Knowledge of the credit cycle, credit appraisal, and rating/decision models.
• Understanding of bank regulations, capital ratios, and credit risk modelling (PD, LGD) with model validation/monitoring experience.
• Familiarity with stress-testing (ICAAP), prudential risk management, and risk data quality.
• Skilled in data visualization, statistical concepts (Monte Carlo, credit transition matrices), and reporting.
• Proficient in Excel (error-checked spreadsheets); experience with MS Access, SQL, R, and Python.