Senior Consultant, Model Validation
Hybrid · Vancouver, British Columbia, Canada
Job Summary
Senior Consultant, Model Validation responsible for independent validation of complex models across retail and non-retail portfolios, ensuring they are sound, well-governed, and aligned with regulatory expectations and our Model Risk Management Framework. Lead validation of models across credit, capital, liquidity, ALM, and allowances; provide effective challenge to model development teams; translate quantitative findings into clear, data-driven insights for senior leaders; collaborate across Finance, Treasury, Risk, and business partners to improve data quality and controls; communicate model risk findings to senior management and governance committees; support governance activities and inventory maintenance. Requires 8+ years of experience in model validation or quantitative risk analytics, strong knowledge of regulatory expectations, and advanced proficiency with R, Python, and SAS. Preferred assets include FRM/CFA/PRM or similar designations and experience within a regulated Canadian financial institution, across all 3 lines of defense. Hybrid work arrangement with on-site commitments for events and business demands at the Vancouver, BC, Canada head office.
Required Qualifications
- A university graduate degree in a quantitative discipline such as Finance, Economics, Mathematics, Statistics, Engineering, or a related field
- A minimum of 8+ years of experience in model validation, model risk management, or quantitative risk analytics within financial services
- Demonstrated experience validating models across areas such as credit risk, capital, liquidity, ALM, fraud, or allowances
- Strong knowledge of regulatory expectations and industry best practices related to model risk management
- Proficient with statistical or analytical tools including R, Python and SAS used in model development and validation
Desired Qualifications
- Professional designations such as FRM, CFA, PRM, or similar are considered strong assets
- Experience engaging with senior stakeholders and providing effective challenge in a constructive manner
- Advanced proficiency with statistical or analytical tools including R, Python and SAS used in model development and validation
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