Risk Analytics Manager

  • Negotiable
  • Brentwood, England, United Kingdom
  • Permanent, Full time
  • Shawbrook Bank
  • 08 Nov 17 2017-11-08

As Shawbrook continues to grow we are looking to hire a Risk Analytics Manager to join a high performing team within the Group Risk Function. This role provides the SME expertise and substantial hands-on risk modelling know-how to help manage model development projects end-to-end from initialization, development to model implementation.

As Shawbrook continues to grow we are looking to hire a Risk Analytics Manager to join a high performing team within the Group Risk Function. This role provides the SME expertise and substantial hands-on risk modelling know-how to help manage model development projects end-to-end from initialization, development to model implementation. The role will contribute significantly in leveraging data and analytics to optimize risk strategies and decision making through effectively identifying and overcoming data gaps, improving scorecards, credit grading system and IFRS9 impairment scoring engine. The role is also positioned as coaching more junior staff and supporting 1st line business functions on analytics, advisory services and training as required.

Key responsibilities will include the following:

  • Managing projects in developing, enhancing and implementing credit grading systems across the bank.
  • Develop the Bank's standardised process and methodology for risk scorecard, IRB model development.
  • Lead on risk analytics projects to deliver and implement solutions according to specified time schedule.
  • Significantly contribute to developing in-house scorecards, IRB or other risk models throughout the credit lifecycle from application to collection/recovery, develop or calibrate Basel IRB models (PD/LGD/EAD) to satisfy capital requirement. Develop interim solutions for PD/LGD estimates where data remained limited.
  • Develop, validate and update IFRS9 models
  • Use SAS to process, organize and standardize data for analytics purposes

Suitable candidates will have the following experience/qualifications:

  • Degree educated in a strong quantitative discipline such as Applied Mathematics / Statistics, Econometrics, Operational Research or Engineering etc.
  • Deep knowledge in general statistical analysis, predictive modeling and possibly also AI
  • Strong SAS programming skills including Base SAS and Macros
  • Excellent working knowledge and proficiency in statistical analysis, credit scorecard / Basel IRB modeling methodologies