Model Risk Specialist - Fraud Model Validation

In this role, you'll validate and challenge models that support fraud detection, anti-money laundering (AML) risk management, and marketing strategy initiatives across the bank. You'll apply statistical, machine learning, and analytical techniques to assess model performance, identify risks and limitations, and provide independent oversight that helps drive sound, data-driven decisions. Working closely with model developers, business stakeholders, and risk partners, you'll play a key role in strengthening model governance, advancing model risk management practices, and ensuring models are fit for purpose, transparent, and appropriately managed throughout their lifecycle.

Performs validation of models and assesses model risk to confirm model appropriateness and capability for a designated portfolio. Provides effective challenge during model development and communicates decisions regarding model use to the business to ensure transparency and understanding of models and model risks. Assesses model's capabilities, stress points and limitations; assesses the associated model risk and the controls in place to mitigate identified risks.

• Shares technical knowledge of models and validation strategies with team members and stakeholders.
• Supports development and execution of strategic initiatives in collaboration with internal and external stakeholders.
• Breaks down strategic problems, and analyses data and information to provide insights and recommendations.
• Troubleshoots model validation issues with team members and stakeholders.
• Leads or assists with the maintenance, monitoring, measurement & reporting on the status of the model validation portfolio / program to various internal & external stakeholder audiences.
• Supports the development and promotion of a business/group program for model validation.
• Develops validation strategies and plans to ensure appropriate type and level of vetting of models is carried out.
• Independently validates / tests models and their associated assumptions, benchmarks, and supporting documentation against model vesting process, standards, guidelines and principles; assesses the data for model development as well as inputs to the model; compares validation results with model developer results for replicability.
• Identifies deficiencies, conditions for model use, recommends changes, and escalates as required; quantifies model risks, documents outcomes and communicates with stakeholders.
• Identifies where corrective actions are required and escalates per guidelines; monitors and ensures corrective action is taken.
• Provides technical advice and guidance to assigned business/group on implementation of the model vetting framework, and resolution of model risk issues.
• Develops and maintains in-depth knowledge of business and related risk management requirements and legislative/ regulatory directives and guidance.
• Builds effective relationships with internal/external stakeholders.
• Ensures alignment between stakeholders.
• Monitors and tracks performance; addresses any issues.
• Coordinates and monitors the review and sign-off of model validation reporting including model inventory and model inventory attestations.
• Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
• Exercises judgment to identify, diagnose, and solve problems within given rules.
• Works independently on a range of complex tasks, which may include unique situations.
• Broader work or accountabilities may be assigned as needed.

Qualifications:

• Typically between 1-3 years of relevant experience and a Master's degree in Statistics, Mathematics, Data Science, Machine Learning, Computer Science, Engineering, Economics, or a related quantitative discipline, with a foundation in statistical analysis, modeling, and data-driven problem solving, or an equivalent combination of education and experience.
• Knowledge and understanding of the model life cycle, model risk management practices.
• In-depth knowledge & experience with risk policy frameworks; quality control / testing frameworks.
• Technical proficiency gained through education and/or business experience.
• Verbal & written communication skills - In-depth.
• Collaboration & team skills - In-depth.
• Analytical and problem solving skills - In-depth.
• Influence skills - In-depth.
• Data driven decision making - In-depth.