Associate/AVP - Stress Testing - Model Validation - BFS

Position Description:

Model Risk Management's mission is to manage, independently and actively, model risk globally in line with the bank's risk appetite with responsibility for:

- Performing robust independent model validation;

- Ensuring early and proactive identification of Model Risks;

- Designing and recommending Model Risk Appetite;

- Effectively managing and mitigating Model Risks;

- Establishing Model Risk metrics;

- Designing and implementing a strong Model Risk Management and governance framework;

- Creating bank-wide Model Risk related policies.

The role is a Model Validator within the Stress Testing team, which is responsible for model risk management for the model used for PnL stress testing, CCAR and EBA as well as revaluation approaches used across Risk models.

Position Specific Responsibilities and Accountabilities:

- Independently review and challenge the methodologies used to generate scenarios and revalue positions, in particular in the space of PnL stress testing and Value at Risk (incl. recalibration, shock smoothening methodologies etc)

- Review and challenge the mathematical/theoretical soundness of the model, check independently its implementation, and assess its suitability for the quantity modelled

- Adhere to the testing framework and augment with expert judgment tests to identify model boundary conditions

- Engage with model developers and owners and communicate in a structured manner with wider model risk stakeholders on every aspect of the model risk management lifecycle e.g model developer documentation submissions, validation outcomes, compensating controls, model risk assessment etc.

- Actively engage in the on-going review of model performance and applicability as well as the validation and review of model changes

Experience/ Exposure

- Model validation, other quantitative risk management role or Front Office quantitative discipline

- Excellent mathematical ability with a strong background in stochastic calculus, partial differential equations, Monte-Carlo methods, finite difference methods, numerical algorithms and statistical methods

- Strong understanding in financial markets (especially derivative pricing), demonstrated by qualifications and experience

- Understanding of stress testing and VAR methodologies or cross-asset pricing models (beneficial)

- Experience in coding in Python in a managed codebase or equivalent languages

- Excellent communication skills - both written and oral

- Self-motivated and proactive

Education/ Qualifications : 

- Post-graduate qualification (or equivalent qualification / work experience) in a numerate subject such as Mathematics, Physics, Statistics, Finance (PhD or equivalent is not required but would be beneficial)