Senior Manager, Model Validation

The Senior Manager, Model Validation reports to the Director, Model Risk Management, and supports the Director and the VP, Model Risk Management, with respect to all aspects of model validation activities within the Bank. The incumbent is responsible for assisting in the development of strategies to validate models through effective challenge and for executing the related validation procedures. The incumbent will also be responsible for ensuring model risk is appropriately managed in accordance with the Bank’s Model Risk Management Framework and applicable regulatory requirements. This includes models for credit and treasury risk management (such as AIRB and IFRS 9 ECL models, interest), interest rate risk, liquidity, and stress testing approaches used to support ICAAP.
The incumbent will be instrumental in fostering relationships with model risk stakeholders. The scope of work includes validating model methodology, evaluating the reasonableness of assumptions, identifying the model effective range of use, limitations, assessing the quality of model inputs, developing benchmark analysis, articulating and communicating identified issues and recommendations, drawing conclusions, and creating model validation reports in accordance to the Bank’s Model Risk Management Framework (MRMF). The incumbent’s primary focus will be on conducting model validation activities. The incumbent may also support model governance activities, such as self-assessments against regulatory guidance and requirements, as well as risk reporting.

Develop model Elaborate model validation strategies and maintain model validation plans.

Assess the appropriateness of the model framework with respect to current or planned use, its assumptions, mathematical implementation, underlying data, and system implementation.

Assess the modeling data from extraction to preparation, cleansing, and treatment for model development suitability. Review and conduct model testing, including outcome analysis through sensitivity, scenario, and stress testing; conduct benchmark analysis; review implementation and user acceptance testing.

Produce validation reports in accordance with the MRMF, including the identification of model limitations, weaknesses, effective range of model use, and assess the level of model risk according to the MRMF principles.

Ensure effective communication with model risk stakeholders by setting expectations, obtaining and providing model-related information, and communicating model risk issues and independent recommendations during the validation process.

Support model governance by ensuring that model metadata is captured and tracked accurately in the model risk management system, and support other model governance related activities such as annual model attestation or model risk reporting.

Stay current with industry trends and practices in model risk management and act as a sounding board for model risk stakeholders.

Educate, influence, and hold accountable key stakeholders accountable for managing model risk in accordance with the Bank’s MRMF and relevant regulatory guidelines.

Provide independent feedback to model developers and/or risk management groups during model development to proactively identify and remediate model risk issues. Such input should be managed effectively to ensure that Model Validation independence is not compromised. 

Promote knowledge sharing. In their capacity, the incumbent may provide supervision to more junior validators.

Develop and maintain effective relationships with model risk stakeholders across the Bank, and act as a trusted advisor regarding model risk management.

Escalate difficult or complex project-related issues, as appropriate.

A Master’s degree or higher in Mathematics, Mathematical Finance, Statistics, Physics, Engineering, Economics, or an equivalent quantitative discipline.

Minimum of 5 years of experience (7 years preferred) in quantitative modeling and/or model validation within the financial industry.

Experience within financial services or another highly regulated environment strongly preferred.

Strong understanding of model risk management and governance.

Strong understanding of risk management principles and practices.

Strong experience with programming languages, which may include Python, R, SAS, C++, C#, Java, and MATLAB. 

Excellent analytical and problem-solving capabilities.

Excellent project management, time management, and organizational skills.

Excellent technical documentation and report-writing skills.

Excellent communication skills.