Credit Suisse - AVP - Model Validation

Position Responsibility:

Be expected to lead and manage independent validation reviews across a wide range of core Risk Capital or other business-impactful models used throughout the bank. Meeting business needs and regulatory expectations with responsibility for investigating key aspects of each model under review: choice of modeling approach, the underlying assumptions and associated limitations, performance and optimal use of the model, etc.

Review, verify and validate risk models for theoretical soundness, testing design and identification of model weaknesses, ensuring ongoing monitoring as well as contribute to the firm-wide model risk and control assessment.

Be expected to demonstrate independence in planning and stakeholder engagement, testing design and execution, results in interpretation and presentation, and the production of documentation strong enough to evidence a sound challenge to both internal and external parties.

The truly global scope of model risk means that this role will involve working with an incredibly broad group of stakeholders from every part of the firm, investigating model risk and model governance standards and performing detailed validation of risk models.

Position Qualification:

Candidates are expected to hold a first degree in a quantitative discipline, e.g. Mathematics, Physics, Engineering, Finance, and probably a Masters or PhD.

Extensive experience in financial modeling and/or model validation. Hands-on experience of risk and capital modeling, derivatives pricing and broader financial modeling is desirable, but regardless of experience, all candidates should be able to demonstrate an understanding of capital modeling, financial and derivative products and mathematics.

Client focus and the ability to communicate effectively with senior stakeholders, including the ability to explain complex topics to a diverse range of audiences.

The experience of managing/leading teams, ideally in the context of model validation and/or financial modeling.

Self-motivation, discipline, task focus, the ability to structure and present work and a proven record of delivering high-quality results to strict deadlines.

Desirable:

Experience in data management and analysis or in Front Office IT would be an advantage.

Good knowledge including programming experience of software applications such as R, Matlab, SQL and SAS.