Manager, Global FC Model Validation

Job Description

As a Manager of Global Financial Crimes Model Validation you will support daily execution within the team to ensure that RBC is maintaining the ongoing effectiveness of Financial Crimes monitoring program. You will report to the Senior Manager of Financial Crime Model Validation as an individual contributor, and will implement and execute substantive financial crimes risk management practices relevant to models and related Frameworks.

This includes the defining and scoping the validation required of new/existing models. You provide continuous close support to Global FC Validation team by implementing successful FC strategies within RBC.

Conduct Model Validation:

• Validate financial crimes models—both machine learning and heuristic-based—to assess output quality, alert effectiveness, and risk mitigation capabilities
• Conduct rigorous testing of sanctions screening and AML detection models to ensure they effectively identify critical financial crimes risks
• Provide comprehensive model risk assessments and challenge recommendations to senior leadership and governance committees
• Manage the Enterprise Model Risk Management (EMRM) inventory system, maintaining robust change management procedures and documentation

Risk Assessment and Proactive Challenges:

• Proactively challenge financial crime models and methodologies.
• Detect and counteract emerging risks related to financial crimes and continuously assess RBC’s risk exposure.

Effective Communication and Documentation:

• Articulate the scope and approach of enterprise-wide model validation to RBC Management, External Regulators, and Internal Audit.
• Develop clear concepts, execute plans efficiently, and deliver organized results.
• Collaborate with FC Model Validation Senior Managers and Directors to make model-related decisions.
• Communicate inherent model risks and limitations effectively.
• Develop and challenge assumptions, conceptual soundness, model performance and process and evaluate metrics during each validation and document results in validation reports.

Innovation and Industry Trends:

• Contribute to research and development with risk-focused techniques.
• Demonstrate key competencies:
  Adaptability, Change Management, Teamwork & Collaboration, Problem Solving, and Planning.
• Establish individual goals, drive performance management, support career development, and reward strong performance.
• Collaborate cross-enterprise teams for better solutions.

• 3+ years in machine learning model development, validation, or financial crimes risk management
• Proficiency in statistical analysis and data manipulation (Python, R, SQL, or SAS)
• Strong knowledge of machine learning algorithms and their applications in financial crimes detection
• Bachelor’s degree in a relevant field (Finance, Data Science, Economics, Mathematics etc.)
• Strong written and oral communication skills; business writing experience
• Knowledge of regulations related to Financial Crimes

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
• Leaders who support your development through coaching and managing opportunities
• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high-performing team
• A world-class training program in financial services
• Opportunities to take on progressively greater scopes of work

Address: 20 KING ST W:

TORONTO

City:
Toronto

Country:
Canada

Work hours/week: 37.5

Employment Type:

Full time

Platform: GROUP RISK MANAGEMENT

Job Type: Regular

Pay Type:

Salaried

Posted Date:

Final date to receive applications:

Note:

Applications will be accepted until 11:59 PM on the day prior to the Final date to receive applications date above.