Senior Manager – Financial Crimes Model Validation

Role Overview

• 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.

Tech Stack

• Python
• SQL

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