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A career as a Model Risk Governance Specialist - AI Governance in the Model Risk Management team at National Bank means acting as a governance specialist for artificial intelligence, machine learning, generative AI and other advanced analytics models.

In this role, you will contribute to the oversight and enhancement of the Bank’s model risk governance framework, with a specific focus on ensuring that AI models and AI-enabled solutions are appropriately identified, assessed, classified, documented, monitored, controlled and reported throughout their lifecycle.

Your job

 As a Model Risk Governance Specialist which a focus on AI Governance, you will:

• Support the development, implementation and continuous enhancement of the Bank’s AI model governance practices for artificial intelligence, machine learning, generative AI, large language models and other emerging model types within the model risk management framework.
• Perform, review and challenge risk assessments for AI models and AI-enabled use cases, considering inherent risk, materiality, complexity, data sensitivity, explainability, usage, business impact, model limitations, control environment and potential customer, operational, compliance or reputational risks.
• Contribute to the development and ongoing enhancement of AI model risk assessment methodologies, including risk-tiering criteria, scoring logic, questionnaires, decision criteria, assessment templates and supporting documentation.
• Help define and maintain lifecycle governance controls for AI use cases, including intake, ownership, documentation standards, approval, validation requirements, ongoing monitoring, human oversight, issue management, escalation and retirement.
• Collaborate with model owners, model developers, validators, technology, data, privacy, cybersecurity, compliance, legal, operational risk and business stakeholders to ensure AI-related risks are identified, assessed and managed in alignment with internal and regulatory requirements.
• Support the integration of AI governance requirements into model inventory and workflow processes, ensuring that AI models and AI-enabled solutions are accurately captured, classified, monitored and reported.
• Monitor changes in the AI model portfolio, including new use cases, material changes, validation outcomes, approval status, monitoring results, remediation actions and model retirements.
• Prepare governance reporting, dashboards and presentations on AI model risk exposure, risk assessment results, portfolio trends, emerging risks, issues and remediation progress for senior management and governance committees.
• Identify governance gaps, control weaknesses and opportunities to improve AI model governance, and recommend practical enhancements to policies, standards, procedures, tools, controls and reporting.
• Support change management activities related to AI governance, including stakeholder communications, training material, implementation support, advisory guidance and adoption monitoring.
• Monitor industry practices, audit observations and evolving expectations related to AI governance and model risk management, and assess their impact on the Bank’s governance framework.
• Promote a strong model risk culture by influencing stakeholders, challenging practices when required and supporting consistent application of AI governance requirements across the organization.

Within the Model Risk Management group, you are part of a team of professionals who provide second line of defence oversight for model risk across the Bank. You report to the Senior Director, Model Risk Governance.

Our team stands out for its analytical rigour, proactive governance mindset, collaborative approach and ability to influence model stakeholders across the Bank.

We ultimately aim to offer you maximum flexibility and quality of life. This notably means a hybrid work environment, as well as adaptable working hours.

The Bank values continuous development and internal mobility. Our personalized training programs enable you to master your job and develop new areas of expertise. Tools such as the Data Academy, language training, the Harvard Learning Center as well as coaching and mentoring support are available to you at all times.

Requirements

• Hold a Bachelor’s degree in finance, economics, mathematics, statistics, engineering, computer science, data science, risk management or a related field and 7 years of relevant experience; OR a master’s degree in a quantitative, finance, technology or risk-related field and 5 years of relevant experience.
• Experience in model risk management, AI governance, risk governance, model validation, quantitative analysis, analytics governance, technology risk, internal audit, compliance or regulatory governance in financial services.
• Strong knowledge of model risk management principles, including model lifecycle governance, model identification, classification, inventory management, validation, approval, monitoring, issue management and reporting.
• Knowledge of AI governance, machine learning models, generative AI risks, responsible AI practices, model explainability, data risk, model limitations and control design.
• Experience performing or reviewing risk assessments, including inherent risk assessments, materiality assessments, risk-tiering methodologies, control assessments or governance reviews.
• Experience contributing to policies, standards, procedures, governance frameworks, risk assessment methodologies, dashboards, management reporting or change management initiatives.
• Strong analytical skills with the ability to synthesize complex information, identify key risks and translate technical topics into clear conclusions, recommendations and action plans.
• Ability to influence and collaborate with senior stakeholders, business lines, model owners, validators, technology teams, risk partners, compliance, legal, cybersecurity, privacy and internal audit.
• Advanced proficiency with Microsoft Office, especially Excel and PowerPoint; experience with data analysis, BI tools, SQL, Python or workflow/GRC platforms is an asset.
• Excellent written and verbal communication skills.