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Investigator supporting Anti - Money Laundering processes at Capital One. Review alerts, conduct research, and document results to ensure compliance with regulations.
About the role
- Senior Manager leading financial crimes model validation at RBC. Collaborating to validate machine learning models and enhance detection capabilities against financial crimes.
Responsibilities
- Lead and mentor a team of model validation specialists, fostering a culture of rigorous challenge and continuous improvement
- Establish and oversee the FC model validation program, ensuring alignment with Enterprise Risk Management (ERM) policies, regulatory requirements, and industry best practices
- Act as a trusted advisor and effective challenger to FC model developers and business users, balancing risk governance with business enablement
- 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
- Provide actionable, data-driven recommendations based on model assessments, contributing to continuous enhancement of FC detection capabilities
- Facilitate remediation of open model risk issues in accordance with regulatory expectations
- Manage metrics, reporting, and dashboard development to track model performance, validation status, and program health
- Collaborate with peers, industry experts, and the Enterprise Model Risk Management team to identify emerging validation themes and trends
- Champion adoption of innovative validation techniques and technologies across the FC program
Requirements
- 5+ years in machine learning model development, validation, or financial crimes risk management
- Proven experience managing teams or leading complex projects in a regulated environment
- Bachelor’s degree in a relevant field (Finance, Data Science, Economics, Mathematics etc.)
- 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
- Familiarity with Enterprise Risk Management governance structures
- Excellent communication skills and ability to work collaboratively.
Benefits
- A comprehensive Total Rewards Program including bonuses and flexible benefits and competitive compensation
- Leaders who support your development through coaching and managing opportunities
- Work in a dynamic, collaborative, progressive, and high-performing team
- Opportunities to do challenging work
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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