AVP/VP - Model Validation/Statistical Modeling - Anti Money Laundering/Assets Liability Management

- The person filling the role is responsible for being model validator for a wide range of IRB and IFRS9 models as well as support other model validation efforts in MTP, IST BoE stress testing frameworks or Anti Money Laundering models etc.

- Provide independent review (IR) and challenge of different aspects of model (conceptual soundness, model performance etc.) across different model types (capital, impairment, liquidity, stress testing etc.) to a high degree of depth, as required by and detailed in the Banks policies and standards. This role will be part of Group Risk IVU team.

- Provide input to/support the governance and reporting processes related to model risk management.

- Work on independent review of diversified set of wholesale models IFRS9, Capital, Liquidity or Stress Testing, Operation, Treasury, Finance models

- Perform technical analyses, data analyses, benchmarking, build challenger models (if needed) to support the validation review and challenge process

- Must be able to challenge others and be open to challenge. Should seek direction on which issues are material but have own views on this also.

- Produce high quality model validation reports, with a particular focus on noting limitations, weaknesses and assumptions

- Self-study of developments in modelling and validation techniques;

- Should have wholesale portfolio knowledge

- Support team members in model validation and review their work

- Strong analytical skills with experience in developing, validating and risk management of models

- Significant experience of coding in R/SQL/C++/Python or equivalent language, including handling large datasets and writing functions.

- Good communication and influencing skills, ability to produce high quality written communication for technical and non-technical audiences.

- Highly organised in terms of documentation and follow through.

- Advanced understanding of the quantitative techniques used in developing and validating PD, LGD, EAD, Machine Learning, VAR, Low Default Portfolio modelling etc.

- An ability to identify and analyse appropriate external data sources for model development or validation.

- Should have relevant experience in analytical industry. Hands-on experience in the use of statistical packages, such as SAS, R, Python. Expert user of Microsoft Excel and other Microsoft Office tools.

- Preferred - Experience in a modeller/validator role in the Wholesale industry. Experience in Machine Learning models

- Beyond risk management, knowledge in financial projection, capital management and treasury