Quantitative Modeling Analyst – AML

Jobtailor; Illinois; On-site; USD 120,000 - 170,000; Full time

Job summary

Jobtailor is seeking a senior analyst to monitor AML Transaction Monitoring models, perform quantitative analyses, and drive model risk assessments. You will review model behavior, test performance, and collaborate with model owners, auditors, and leadership to manage emerging risks.

Applicants should have strong SAS/SQL/Python skills, experience in regulated environments, and the ability to work from a U.S. Bank location three or more days per week.

Qualifications

• Bachelor’s degree in a quantitative field with at least 8 years of relevant experience, or MA/MS with five+ years, or PhD with four+ years.
• Experience evaluating quantitative models, analytics, or monitoring frameworks in a regulated environment.
• Strong understanding of model risk concepts, quantitative modeling, model drivers, segmentation strategies, threshold optimization, performance monitoring, sampling methodologies, and root cause analysis.
• Ability to analyze complex datasets, conduct statistical assessments and exploratory research, and translate findings into actionable insights.
• Proficiency in SAS, SQL, and Python for data analysis, testing, automation, and code review.
• Experience supporting AML/BSA Transaction Monitoring systems or financial crime detection tools.
• Understanding of AML best practices and regulatory expectations.
• Ability to evaluate code logic, data inputs, transformations, and outputs against documented intent.
• Strong written and verbal communication skills.
• Ability to work independently and manage multiple priorities in a fast-paced environment.
• Self-directed problem-solving ability and attention to detail.
• Must be able to work from a U.S. Bank location three or more days per week
• Not eligible for current or future visa sponsorship
• Ability to comply with U.S. Bank policies, procedures, Code of Ethics and Business Conduct, and workplace conduct and safety policies

Responsibilities

• Perform ongoing monitoring and performance assessments of AML Transaction Monitoring models.
• Conduct in-depth analytical research into model performance and behavior changes, including alert volumes, customer populations, and transaction patterns.
• Execute and document periodic testing and performance reviews aligned with regulatory expectations and internal risk standards.
• Review and challenge model behavior, limitations, and assumptions; identify control gaps and recommend remediation.
• Conduct comprehensive code reviews and code change assessments for AML Transaction Monitoring models.
• Provide constructive feedback to model and code owners to support issue resolution and continuous improvement.
• Assess model threshold and sampling soundness through Below-the-Line reviews and support calibration decisions.
• Prepare and present materials for senior leadership, Model Risk Management, Corporate Audit, and regulatory partners.
• Partner with model owners, Model Risk Management, auditors, and senior leadership to evaluate model behavior and emerging risks.
• Document analyses and conclusions so work can be independently understood, reviewed, and defended.

Skills

Quantitative analysis

SAS proficiency

SQL proficiency

Python proficiency

Model risk concepts

Data analysis

Communication skills

Independent work

Education

Bachelor’s degree in a quantitative field

MA/MS in a quantitative field

PhD in a quantitative field

Tools

SAS

SQL

Python

Job description

Perform ongoing monitoring and performance assessments of AML Transaction Monitoring models
Conduct in-depth analytical research into model performance and behavior changes, including alert volumes, customer populations, and transaction patterns
Execute and document periodic testing and performance reviews aligned with regulatory expectations and internal risk standards
Review and challenge model behavior, limitations, and assumptions; identify control gaps and recommend remediation
Conduct comprehensive code reviews and code change assessments for AML Transaction Monitoring models
Provide constructive feedback to model and code owners to support issue resolution and continuous improvement
Assess model threshold and sampling soundness through Below-the-Line reviews and support calibration decisions
Prepare and present materials for senior leadership, Model Risk Management, Corporate Audit, and regulatory partners
Partner with model owners, Model Risk Management, auditors, and senior leadership to evaluate model behavior and emerging risks
Document analyses and conclusions so work can be independently understood, reviewed, and defended

Requirements

• Bachelor’s degree in a quantitative field with at least 8 years of relevant experience, or MA/MS in a quantitative field with five or more years of related experience, or PhD in a quantitative field with four or more years of related experience
• Experience evaluating quantitative models, analytics, or monitoring frameworks in a regulated environment
• Strong understanding of model risk concepts, quantitative modeling, model drivers, segmentation strategies, threshold optimization, performance monitoring, sampling methodologies, and root cause analysis
• Demonstrated ability to analyze complex datasets, conduct statistical assessments and exploratory research, and translate findings into actionable insights
• Proficiency in SAS, SQL, and Python for data analysis, testing, automation, and code review
• Experience supporting AML/BSA Transaction Monitoring systems or financial crime detection tools
• Understanding of AML best practices and regulatory expectations
• Ability to evaluate code logic, data inputs, transformations, and outputs against documented intent
• Strong written and verbal communication skills
• Ability to work independently and manage multiple priorities in a fast-paced environment
• Self-directed problem-solving ability and attention to detail
• Must be able to work from a U.S. Bank location three or more days per week
• Not eligible for current or future visa sponsorship
• Ability to comply with U.S. Bank policies, procedures, Code of Ethics and Business Conduct, and workplace conduct and safety policies

Core Competencies

Demonstrates expertise in evaluating and monitoring AML Transaction Monitoring models, with strong capabilities in quantitative analysis, model risk assessment, and regulatory compliance. Proficient in data analysis using SAS, SQL, and Python, with a focus on translating complex datasets into actionable insights.

Highest-signal resume keywords

• Model Risk Assessment
• Quantitative Analysis
• SAS Proficiency
• SQL Proficiency
• Python Proficiency

ATS Optimization Keywords

Hard Skills

• Quantitative Modeling
• Performance Monitoring
• Root Cause Analysis
• Statistical Assessments
• Threshold Optimization
• Sampling Methodologies
• Code Review
• Data Analysis
• Exploratory Research
• Alert Volume Analysis

Soft Skills

• Strong Communication Skills
• Self-Directed Problem Solving
• Attention to Detail
• Ability to Manage Multiple Priorities
• Independent Work Capability

Industry Keywords

• AML Best Practices
• Regulatory Expectations
• Model Behavior Evaluation
• Control Gaps Identification
• Model Calibration

Tools & Technologies

• AML Transaction Monitoring Systems
• Financial Crime Detection Tools