Quantitative Model Analyst, Level 2

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

Job summary

Jobtailor is seeking a skilled data science professional to join a financial crime analytics team in Illinois. The role focuses on developing and validating complex statistical models to monitor suspicious activity in U.S.

Bank customer accounts and to support ongoing model lifecycle management. You will own existing models, contribute to new model development, and communicate results to compliance, risk, and technology stakeholders, ensuring alignment with AML regulations and regulatory

Qualifications

• Bachelor’s degree in a quantitative field with 3+ years of related experience, or MA/MS with <3 years.
• Experience with transaction monitoring or financial crime models.
• Advanced knowledge of statistical modeling techniques and validation methodologies.
• Strong programming skills in SAS, Python, or SQL.
• Understanding AML regulations.
• Ability to interpret and communicate complex model behavior to non-technical stakeholders.
• Strong organizational, analytical, and project management skills.
• Ability to work independently and collaboratively across teams.

Responsibilities

• Develop, validate, test, document, and implement complex statistical models to monitor suspicious activity in customer accounts.
• Take ownership of existing models and support development of new models.
• Create/develop models and model documentation.
• Conduct periodic performance assessments, tune/calibrate, and ensure regulatory compliance.
• Communicate model performance, limitations, and findings to stakeholders across compliance, risk, and technology teams.
• Deliver model development artifacts, performance assessments, implementation documentation, and monitoring reports.

Skills

Statistical modeling

Model validation

Data analysis

Communication

Project management

Education

Bachelor’s degree in quantitative field

MA/MS in quantitative field

Tools

SAS

Python

SQL

Job description

Responsibilities

• Develop, validate, test, document, and implement complex statistical models used to monitor suspicious activity within U.S. Bank customer accounts
• Take ownership of existing models and support the development of new models
• Create/develop models and model documentation
• Conduct periodic performance assessments, tune/calibrate, and ensure models meet regulatory expectations
• Communicate model performance, limitations, and findings to stakeholders across compliance, risk, and technology teams
• Deliver model development artifacts, performance assessments, implementation documentation, business requirements for model integration, ongoing monitoring reports, and presentations

Requirements

• Bachelor’s degree in a quantitative field, and three or more years of relevant experience OR
• MA/MS in a quantitative field, and less than three years of related experience
• Experience with internally developed and/or vendor-provided models for transaction monitoring or financial crime detection
• Advanced knowledge of statistical modeling techniques and validation methodologies
• Strong programming skills in SAS, Python, SQL, or similar
• Understanding of AML regulations
• Ability to interpret and communicate complex model behavior to non-technical stakeholders
• Strong organizational, analytical, and project management skills
• Demonstrated ability to work independently and collaboratively across teams