AML Model Validation Manager

Interactive Brokers Group, Inc. (Nasdaq: IBKR) is a global financial services company headquartered in Greenwich, CT, USA, with offices in over 15 countries. We have been at the forefront of financial innovation for over four decades, known for our cutting-edge technology and client commitment.

IBKR affiliates provide global electronic brokerage services around the clock on stocks, options, futures, currencies, bonds, and funds to clients in over 200 countries and territories. We serve individual investors and institutions, including financial advisors, hedge funds and introducing brokers. Our advanced technology, competitive pricing, and global market help our clients to make the most of their investments.

Barron's has recognized Interactive Brokers as the #1 online broker for six consecutive years. Join our dynamic, multi-national team and be a part of a company that simplifies and enhances financial opportunities using state-of-the-art technology.

The AML Model Validation Manager will lead the independent validation of Anti-Money Laundering (AML) and financial crime detection models across global entities. This role will oversee a team of validation professional and ensure regulatory compliance through rigorous model review, testing, and documentation. The position requires deep technical expertise in Python and SQL, combined with strong knowledge of AML/financial crime regulations and model risk management principles.

• Supervise, mentor, and develop a team of 2 model validation analysts
• Assign validation projects based on team capabilities and priorities
• Conduct performance evaluations and provide ongoing coaching and technical guidance
• Foster a culture of continuous learning and technical excellence within the team

• Lead independent validation of models across multiple domains:

• Money Movement/Transaction Monitoring scenarios
• Trade Surveillance models (market abuse, insider trading, manipulation)
• Sanctions screening
• Geographic Risk Rating (GRR) models
• Customer Risk Rating (CRR) models

• Perform comprehensive validation assessments including conceptual soundness, data integrity, model methodology, performance testing, and ongoing monitoring review
• Develop and execute validation test scripts using Python and SQL to assess model accuracy, calibration, and performance
• Validate model assumptions, logic, thresholds, and segmentation approaches
• Assess model governance, documentation, and change management processes

• Extract, manipulate, and analyze large datasets using Python and SQL
• Develop Python scripts for statistical testing, back-testing, and sensitivity analysis
• Replicate model logic and perform independent calculations to verify sample model outputs
• Conduct outcome analysis and effectiveness testing of surveillance alerts
• Perform false positive/false negative analysis and assess model tuning effectiveness
• Validate data quality, completeness, and appropriateness for model inputs

• Ensure validation activities meet regulatory requirements from SR 11-7, OCC 2011-12
• Prepare comprehensive validation reports documenting findings, limitations, and recommendations
• Present validation results to Regional and Global AML senior management
• Support regulatory examinations and respond to regulatory inquiries regarding model validation
• Stay current on regulatory guidance, industry best practices, and emerging AML typologies
• Enhance validation methodologies, tools, and automation capabilities
• Contribute to validation framework development and standard operating procedures

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Finance, or related quantitative field
• 7+ years of experience in model validation, model development, or quantitative analysis
• 3+ years of specific experience in AML/financial crime model validation or development
• 2+ years of people management or team leadership experience
• Deep understanding of AML/BSA regulations, OFAC sanctions, and financial crime typologies
• Knowledge of model risk management frameworks and regulatory guidance (SR 11-7, OCC 2011-12)
• Advanced proficiency in Python and NoSQL for data analysis, statistical testing, and model validation
• Experience working with Pandas and Numpy
• Expert-level SQL skills for complex data extraction, manipulation, and analysis
• Strong statistical and quantitative analysis capabilities
• Self-motivated and able to handle tasks with minimal supervision.
• Superb analytical and problem-solving skills.
• Excellent collaboration and communication (Verbal and written) skills.
• Outstanding organizational and time management skill.