Director leading enterprise data governance, catalog, quality, and AI readiness for CBC/Radio - Canada’s public service media organization. Hybrid role guiding governance programs, councils, stakeholders, and data teams.
About the role
- AI model risk oversight manager at Manulife, an international financial services provider. Challenging governance, validation, and controls for high-risk AI initiatives.
Responsibilities
- Provide independent second-line oversight and challenge of AI model risk management practices, validation outcomes, risk assessments, controls, and monitoring activities
- Review medium- and high-risk AI initiatives and assess identification, assessment, mitigation, monitoring, and escalation of model risks
- Evaluate AI and machine learning methodologies, model design, data quality, testing approaches, performance metrics, and monitoring practices
- Assess risks associated with Generative AI, large language models, foundation models, RAG, third-party AI solutions, and Agentic AI applications
- Conduct risk-based reviews, thematic assessments, and sampling activities to identify emerging risks, recurring weaknesses, and portfolio-level concerns
- Evaluate Line 1 validation, governance, monitoring, and risk management outcomes
- Develop and communicate independent opinions, recommendations, and challenge positions supported by evidence and risk analysis
- Produce executive-ready risk assessments, management reporting, thematic reviews, and governance committee materials
- Translate complex technical findings into clear business, governance, and risk implications for senior stakeholders
- Contribute to enhancing AI model risk management policies, methodologies, training materials, and oversight practices
Requirements
- 7+ years of relevant experience for Manager-level candidates or 10+ years for Senior Manager-level candidates
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, Risk Management, Business, or a related discipline
- Experience in AI, Data Science, Machine Learning, Model Risk Management, Model Validation, Technology Risk, Analytics Risk, or related disciplines
- Experience reviewing technical documentation, model validation results, testing evidence, monitoring outcomes, and risk assessments
- Strong understanding of AI model lifecycle management, model risk concepts, governance practices, and control frameworks
- Experience working with AI and machine learning solutions within financial services or another highly regulated industry
- Ability to challenge technical stakeholders and influence senior leaders
- Bilingualism (English and French) is a strong asset; if the successful candidate is in Québec, proficiency in both languages will be required
- Advanced understanding of AI Model Risk Management frameworks and model lifecycle governance
- Experience assessing Generative AI, large language models, foundation models, RAG, and Agentic AI risks
- Practical familiarity with Python, SQL, R, machine learning environments, or analytical tools
- Experience conducting model reviews, validation activities, independent challenge, or technical risk assessments
- Knowledge of responsible AI principles, explainability, fairness, bias management, robustness, and model monitoring practices
- Familiarity with emerging regulatory requirements and industry standards relating to AI, model risk, and technology risk management
- Experience preparing executive reporting, governance committee materials, or portfolio-level risk insights
Benefits
- Flexible work environment
- Learning and career growth support
- Well-being and inclusion support
- Health insurance
- Dental insurance
- Mental health benefits
- Vision insurance
- Short- and long-term disability insurance
- Life and AD&D insurance
- Adoption/surrogacy benefits
- Wellness benefits
- Employee/family assistance plans
- Retirement savings plans
- Pension
- Global share ownership plan with employer matching contributions
- Financial education and counseling resources
- Paid holidays, vacation, personal, and sick days
- Statutory leaves of absence
- Incentive programs and incentive compensation tied to business and individual performance
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