AI Risk Analyst

BMO•Toronto, ON

2d•CA$61,600 - CA$113,900•Onsite

About The Position

Provides oversight, monitoring and reporting on operational risks for a designated portfolio. Develops and monitors the operational management framework that includes the governance framework & practices leveraged across BMO to manage operational risks. Provides policies & standards, methodologies and controls that increase transparency, accuracy and consistency across groups. Works with stakeholders to implement the methodology, metrics and program standards for the assigned portfolio to ensure compliance as well as effective monitoring, timely reporting and identification of action plans.

Requirements

Develops and maintains working knowledge of AI risk, operational risk, and relevant regulatory expectations.
Builds effective working relationships with internal stakeholders and corporate support areas.
Exercises judgment to identify and resolve problems within defined guidelines; escalates complex or ambiguous issues.
Works independently on assigned tasks, including those those involving non-routine or evolving requirements.

Nice To Haves

Experience with Power Platform, workflow tools, or data pipelines.

Responsibilities

Supports the design, development, and implementation of automation solutions across the AI risk lifecycle and broader risk oversight activities.
Builds, tests, maintains, and documents workflow automation solutions (e.g., Power Platform, workflow tools, data pipelines) under direction of senior team members.
Identifies and implements opportunities to reduce manual effort, improve data quality, and enhance process efficiency and scalability.
Maintains end-to-end documentation of workflows and processes to support auditability, traceability, and repeatability.
Produces and manages structured datasets to support risk oversight, monitoring, and reporting activities.
Supports data quality management, including validation, standardization, and remediation of data gaps.
Assists in the development of reporting outputs, dashboards, and metrics, ensuring consistency with data governance standards.
Analyzes data to identify trends, process gaps, and potential risk impacts related to AI use cases and other risk initiatives.
Supports execution of AI risk officer activities, including intake review, portfolio monitoring, and use case assessments, as assigned.
Performs initial analysis of new initiatives or workflows to identify potential risk considerations, escalating to senior team members as appropriate.
Assists with the interpretation of regulatory requirements and internal policies, and their application to governance frameworks and processes.
Supports execution of second line of defense (2LOD) oversight activities, ensuring alignment with established risk frameworks and standards.
Supports the execution of governance and oversight processes, including reporting, attestations, and tracking of action items.
Assists with governance forums and working groups, including coordination of materials, documentation, and follow-ups.
Contributes to change management activities, primarily focused on execution, implementation, and sustainment.
Supports the development of training materials, user guidance, and communication artifacts to improve adoption and consistency.
Works with stakeholders to improve transparency, consistency, and usability of processes, metrics, and reporting outputs.
Administers and maintains risk program activities in accordance with policies, standards, and established procedures.
Monitors and tracks workflow performance, identifying and addressing operational issues.
Maintains tools, templates, and supporting artifacts used across risk programs (e.g., RCSA, regulatory tracking, inventory management), as required.
Develops and maintains working knowledge of AI risk, operational risk, and relevant regulatory expectations.
Builds effective working relationships with internal stakeholders and corporate support areas.
Exercises judgment to identify and resolve problems within defined guidelines; escalates complex or ambiguous issues.
Works independently on assigned tasks, including those involving non-routine or evolving requirements.
Supports additional AI risk and adjacent risk activities as required, based on evolving priorities and regulatory expectations.