Description
A career as senior director analytics in the Credit Risk Analytics team at National Bank means acting as a leader in credit risk model development and governance. This role allows you to have a positive impact on the organization by leveraging your expertise in credit risk analytics, regulatory frameworks, and advanced modeling to support sound decision-making and robust risk management practices.
Your role
- Mobilize, develop and lead the team of experts in model development performance monitoring, back-testing and benchmarking.
- Lead the development and evolution of IFRS 9 credit risk models, including probability of default, loss given default, exposure at default, and staging models for Retail and Wholesale portfolios
- Oversee model performance monitoring activities, including back-testing, benchmarking, and readiness for validation
- Define and execute the roadmap for model recalibration, enhancement, and continuous improvement in line with regulatory expectations
- Present model methodologies, assumptions, limitations, and risk impacts to senior management and model oversight committees
- Collaborate with internal partners to support model review, approval, and governance processes
- Ensure compliance with internal model risk management policies, IFRS 9 standards, and regulatory requirements, including the resolution of validation, audit, and regulatory findings
Your team
The Credit Risk Analytics sector brings together specialists who work in an agile, proactive, and collaborative manner to strengthen the Bank’s credit risk framework and analytical capabilities.
Within the Credit Risk Analytics department, you are part of a large team of professionals and report to a senior director. The team stands out for its expertise in model development, implementation, and risk reporting across IFRS 9, stress testing, and capital domains.
The Bank values continuous development and internal mobility. Our personalized training programs, based on learning through action, allow you to master your role and develop new areas of expertise. Tools such as the Data Academy, language training, the Harvard Learning Center, and coaching and mentoring support are available to you at all times.
Prerequisites
- Hold a diploma in relevant fields such as financial engineering, finance, economics, statistics, mathematics, computer science, or data science
- Have 7 to 10 years of experience in credit risk modeling or model validation within a major financial institution in Canada
- Demonstrate strong expertise in credit risk modeling methodologies, data requirements, performance metrics, model limitations, and compensating controls
- Have solid knowledge of IFRS 9 requirements and regulatory guidelines related to credit risk, loan allowances, and stress testing
- Be familiar with model risk management frameworks and governance processes
