AI Governance Consultant - Wealth Analytics for Major Canadian Banking Client

AI Governance Consultant - Wealth Management

Role Summary

This contract role supports the 1st Line of Defense AI Governance program by leading and executing intake, triage, documentation, and risk/control assessment activities for AI use cases across Wealth Management. The successful candidate will help ensure AI initiatives align with the Enterprise AI Risk Directive expectations (e.g., lifecycle governance, evidence, inventory, monitoring, and escalation), and will work closely with business, technology, and data science teams to embed responsible AI practices across the AI lifecycle.

This role requires a blend of AI/ML technical literacy, risk and governance experience, strong stakeholder management, and the ability to produce audit-ready documentation and reporting.

Key Responsibilities

1) AI Use Case Intake, Triage & Risk Assessment (1LOD)

• Lead the intake and triage of AI initiatives and support progression through required governance gates (e.g., PoC, pilot, implementation, monitoring, retirement).
• Assess AI risks and required controls in collaboration with initiative owners, data science, and technology teams; identify gaps and drive closure plans.
• Support/prepare documentation for governance checkpoints and facilitate appropriate escalations through 1LOD oversight forums as needed.

2) Governance Program Execution & Lifecycle Oversight

• Support execution of the local AI governance program, including stakeholder engagement, issue escalation, lifecycle oversight, and change management practices
• Ensure use cases have defined performance measures and monitoring plans, and that action plans are in place if performance falls below acceptable thresholds.

3) Inventory, Controls & Evidence Management

• Maintain and reconcile inventories of AI use cases and associated controls; ensure documentation remains current, accessible, and “audit-ready.”
• Support alignment of Process Risk Controls (PRCs) and local control libraries to enterprise minimum expectations, and help track compliance/attestation activities.
• Contribute to enterprise reporting processes (including metrics reporting) and maintain traceability to governance requirements and lifecycle stage.

4) Reporting, Metrics & Executive Materials

• Track and report governance KPIs and prepare concise updates for relevant 1LOD and enterprise oversight stakeholders.
• Draft governance-ready materials (e.g., recommendations, approvals, summaries) that are clear, defensible, and fit for senior audiences.

5) Collaboration & Advisory (Business + Tech + Data Science)

• Act as a liaison between business owners, technology partners, and data science teams to standardize governance practices and ensure consistent application of risk controls across initiatives.
• Review AI solutions for risks such as explainability, human oversight expectations, disclosure concerns, and investor/client harm considerations (as applicable), and recommend mitigating controls.

Required Qualifications

• Bachelor’s degree in a relevant field (e.g., Data Science, Computer Science, Engineering, Risk/Compliance, Analytics); advanced degree is an asset.
• 5+ years’ experience across one or more of: AI/ML implementation, model risk management, model governance, technology risk, data science, or risk/compliance within a regulated environment.
• Working knowledge of AI/ML concepts and lifecycle stages (PoC pilot production monitoring/decommission) and ability to challenge documentation quality and control completeness.
• Strong understanding of AI risk governance expectations, including lifecycle governance, inventory management, monitoring, and evidence/audit readiness.
• Excellent stakeholder management and written communication skills (able to produce executive-ready summaries and defensible governance documentation).

Preferred / Nice-to-Have

• Experience operating in a 1LOD AI governance or enterprise governance program model (or similar risk framework operating model).
• Familiarity with centralized AI inventory “book of record” concepts and enterprise reporting practices.
• Experience with governance tooling, control libraries/PRCs, and structured documentation management.

Key Behaviors

• Strong analytical skills and ability to translate ambiguity into structured governance actions.
• Confident, pragmatic “risk + delivery” mindset: balances enablement with control rigor.
• Clear communicator who can influence across business, tech, and data science teams.
• High accountability for documentation quality and audit defensibility.