AML Transaction Monitoring Director

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed.  We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One.

Job Description

This senior position will oversee assessment, design, development, and documentation of the AML/BSA- transaction monitoring program for the Enterprise Financial Crimes Compliance (EFCC) Financial Intelligence Unit (FIU). Beyond the creation and support of models to effectively detect potentially suspicious activity, a key criterion of success within this role is the ability to meet the standards of internal testing, audit reviews, and regulatory exams; the Monitoring Management & Development team must compile compelling evidence to demonstrate the effectiveness of each model, data completeness and quality, and technological concepts employed by the FIU. The candidate must have proven subject matter expertise in financial products and services as well as AML analytics and modeling. The individual should be technologically confident and familiar with model risk management principles.

This position will lead a team responsible for the creation and execution of U.S. Bank’s systemic transaction monitoring program, including managing the lifecycle of new models required to mitigate risks of high-risk products, customers, and transaction channels. The chosen candidate will be a highly visible leader who will help shape the vision and strategy around next-generation monitoring. An executive presence, excellent communication, hands-on leadership, and influencing skills are essential to success in this role.

ESSENTIAL FUNCTIONS

• Manage and coach a team of Quantitative Analysts responsible for development and continuous improvement of all AML transaction monitoring models.  
• Work with partners to identify new and emerging AML threats, and nimbly adapt U.S. Bank’s monitoring practices.
• Define data requirements and ensure data appropriateness for effective modeling.
• Manage communication and responses to internal audit, validation, and outside government agency partners in explaining modeling processes supporting AML functions.
• Lead efforts to thoroughly satisfy and document all programmatic efforts to ensure that U.S. Bank meets OCC 2011-12 expectations and internal Model Validation standards.
• Collaborate with Risk and Business Line partners to evaluate the risks of new products, services, and portfolios, and design risk-based transaction monitoring solutions.
• Ensure the team is working continually to implement new processes or techniques to improve programs to be as efficient as possible while effectively mitigating risk.
• Explore ML/AI techniques to enhance process efficiency.
• Deliver presentations on key projects and emerging risks to senior leaders and regulatory stakeholders.

Basic Qualifications

• Bachelor’s degree in a relevant field
• 15 years of experience in an applicable risk management environment, financial modeling, data science or relevant field

Preferred Qualifications

Educational Background and Experience:

• Advanced technical degree including Master or PhD in a quantitative discipline (e.g., economics, statistics, mathematics, engineering, computer science)
• 10 or more years of relevant experience in an AML/BSA analytical environment
• Knowledge of financial services environment and banking products, policies, operations, and applicable procedures

Technical Skills:

• Subject matter expertise and significant development experience using SQL, SAS, Python or R

• Familiar with standard AML transaction monitoring vendor solutions such as NICE Actimize, Oracle Mantas and/or SAS AML
• Advanced data compilation, programming skills and qualitative analysis skills
• Experience with cloud-based tools and infrastructure (Azure or AWS)
• Hands-on experience with generative AI and a working knowledge of its applications

Analytical and Problem-Solving Skills:

• Skilled in detecting, remediating, and preventing data quality issues

• Experience in statistics, numerical methods, optimization, and operations combined with extensive experience within the financial services sector
• Understanding of standard statistical methods for the identification of outlier events; linear or logistic regression; natural