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Interim Credit Risk Modeller

  • Location:

    Nottingham

  • Sector:

    Risk & Compliance

  • Job type:

    Temporary

  • Salary:

    £400 - £800 per day

  • Contact:

    Rachel Nelson

  • Contact email:

    rachel.nelson@oliverjames.com

  • Job ref:

    JOB-072021-146915_1626789274

  • Published:

    12 days ago

  • Duration:

    6 Months

  • Expiry date:

    2021-08-19

  • Startdate:

    ASAP

  1. Manage the day-to-day maintenance of credit risk models, enhancing existing and developing new models in the Credit Risk function to monitor current and emerging risks, offer critical insight and provide recommendation on lending strategy
  2. Support the Credit Risk Manager in identifying processes that can be improved and made more efficient and provide a strategic pathway for implementation of new approaches
  3. Design interactive dashboards and analytical tools for the purposes of forecasting, scenario analysis and stress testing
  4. Produce reports based on model outputs, ensuring a high standard of accuracy and presentation and supporting the Credit Risk Manager in highlighting any areas that require further analysis or commentary, raising any areas for concern to senior management
  5. Propose and run model developments in line with our Risk Policy and oversight from the Credit Risk Manager, including the usage of data, analytical techniques, governance and documentation
  6. Support the Credit Risk Manager with the management of existing models in the Model Inventory along the principles of the Model Risk Policy, including monitoring, reviewing risk triggers and ensuring reviews are carried out on schedule
  7. Assist the Credit Risk Manager in any second line risk, internal audit or external audit reviews of model developments or governance
  8. Involvement in modelling projects in new areas such as climate risks, customer churn prediction and risk-based pricing, identifying opportunities for model development and a more data-driven approach
  9. Remain up to date with developments in data science, scoping innovative ways to harness the potential of customer data (e.g. via open banking) to produce more accurate forecasts, deliver more tailored products and optimise the mortgage lending strategy

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