This role pays less than
86%
of similar roles. Most pay
$162,000–$246,675
— the shaded band above.
At the midpoint, this role pays about
$145k
versus about
$204k
for comparable roles.
Based on 240 similar postings.
Employer
About US Bank
U.S. Bank (U.S. Bancorp) is the fifth-largest bank in the United States, providing retail banking, corporate and commercial banking, wealth management, and payment services to millions of customers. Industry: Banking & Financial Services
US Bank currently has
39 open roles
on FindRole.
Listed pay typically runs
$111,605–$131,300
across 34 roles with salary data.
The Quantitative Modeler Manager - AML joins the Financial Intelligence Unit team to support the development, production, and maintenance of Anti-Money Laundering transaction monitoring systems. This individual will manage the full model-development lifecycle, including data exploration, pilot testing, and moving models into production while ensuring compliance with Model Risk Governance standards. The role involves advancing the program toward sophisticated anomaly detection systems using machine learning modeling approaches. Key responsibilities include creating technical documentation, performing performance monitoring through Below the Line testing, and defending design decisions to internal and external regulators. The candidate will utilize SAS, SQL, and Python to develop models while applying regression techniques, time series analysis, and various statistical methods. This position addresses critical financial crime compliance by managing complex risk factors and ensuring adherence to regulatory rules within the transaction monitoring domain.
Develop, produce, and maintain Anti-Money Laundering (AML) transaction monitoring systems using SAS, SQL, and Python.
Drive the full model development lifecycle from initial data exploration to pilot testing and production.
Create robust technical documentation that meets specific Model Risk Governance standards for internal and external review.
Perform ongoing model monitoring through research, analysis of performance metrics, and Below the Line testing.
Defend modeling methodologies and design decisions to internal audit teams, regulators, and other stakeholders.
Translate complex machine learning concepts into clear explanations for various audiences including senior leadership and examiners.
What we're looking for
Bachelor's degree in a quantitative field and 10 or more years of relevant experience.
MA/MS in a quantitative field and six or more years of related experience.
PhD in a quantitative field and five or more years of related experience.
Experience developing BSA/AML monitoring applications and related professional documentation.
Expertise in true machine learning modeling approaches.
Extensive knowledge of regression techniques, parametric and non-parametric algorithms, time series techniques, and other statistical models (preferred).
Advanced data compilation, programming skills, and qualitative analysis skills (preferred).
Thorough knowledge of applicable regulatory rules, guidance, or supervisory letters (preferred).
Python
SQL
SAS
R
Spark
Machine Learning
Statistical Modeling
Big Data
Data Analysis
Feature Engineering
Model Governance
Stress Testing
CECL
Portfolio Management
Risk Management