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Risk Manager Model Implementation

  • Location: Milton Keynes
  • Salary: 60,000 - 80,000 per year
  • Job Type:Permanent

Posted about 1 month ago

  • Sector: Credit Risk & Analytics
  • Contact: Eleanore Sykes
  • Contact Email: esykes@merje.com
  • Contact Phone: 0161 883 2750
  • Expiry Date: 08 June 2023
  • Job Ref: 10269

Risk Manager - Model Implementation

Milton Keynes 2 days per week

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Within the Santander UK Risk Division, the Provisions & Forecasting team is responsible for estimating credit loss reserves and for forecasting future credit losses over a range of different scenarios and time horizons.

This is a great opportunity to join a team is responsible for the maintenance and execution of the full suite of credit impairment models as well as DoD (Definition of default) engines and plays a key role in the determination of credit loss budgets for Santander UK and provides the credit loss projections used in internal and external stress testing exercises including those requested by regulatory authorities.

The difference you'll make

  • Overseeing engine execution to produce DoD (Definition of default) model output.
  • Supporting change process and implementation of new models
  • Keeping process documentation up to date with model changes
  • Reviewing and challenging of the next generation credit risk provisioning models.
  • Ensuring models and model outputs are subject to appropriate governance.
  • Actively seeks to either reduce or remove risk when weaknesses in either the methodology or the processes are identified.
  • Preparing materials and presenting results to governance forum/committees

What you'll bring

  • Experience with building and running models in SAS or similar statistical software or programming languages.
  • Experience in providing data and logic specifications to IT teams

It would also be nice for you to have

  • In depth knowledge of IFRS9 provisioning methodologies, default guidelines and risk governance processes.
  • Ability to develop and explain to senior management complex credit risks and how such risk can be mitigated.

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