Senior Quantitative Modeling Lead – AML & ML

U.S. Bank; Chicago (IL); On-site; USD 133,000 - 157,000; Full time

Benefits offered by this job

Healthcare (medical, dental, vision)

401(k) and retirement plan

Paid vacation

Up to 11 paid holiday opportunities

Sick and Safe Leave

Job summary

U.S. Bank is seeking an experienced professional to support the development, production, and ongoing maintenance of AML transaction monitoring systems, including Actimize SAM and internally developed models using SAS/SQL/Python.

You will lead the full model-development lifecycle, create governance documentation, and communicate complex concepts to diverse audiences, collaborating with EFCC, Model Risk, and external reviewers.

Qualifications

• Bachelor’s degree in a quantitative field and 10+ years of relevant experience
• MA/MS in a quantitative field and six+ years of related experience
• PhD in a quantitative field and five+ years of related experience

Responsibilities

• Partner with EFCC and FIU to understand transaction monitoring apps, approaches and processes
• Support/own/enhance existing models
• Drive full model-development lifecycle from data exploration to production
• Create robust model development documentation per Model Risk Governance standards
• Monitor models in partnership with FIU team with performance metrics and testing
• Defend modeling approaches to internal and external examiners

Skills

Regression techniques

Time series techniques

Model validation tests

Python

SAS

Communication skills

Leadership

Analytical skills

Education

Bachelor's degree in quantitative field

MA/MS in quantitative field

PhD in quantitative field

Tools

SAS

Python

SQL

Job description

U.S. Bank is seeking an experienced professional to support the development, production, and ongoing maintenance of AML transaction monitoring systems, including Actimize SAM and internally developed models using SAS/SQL/Python.

You will lead the full model-development lifecycle, create governance documentation, and communicate complex concepts to diverse audiences, collaborating with EFCC, Model Risk, and external reviewers.