Integration and Automation Leader - Credit Risk Modeling

US Bank

Hybrid

Quick summary

Work type
Hybrid
Location
Minneapolis, MN · Chicago, IL · Charlotte, NC · San Francisco, CA · Los Angeles, CA
Salary
$133,365–$156,900 / yr
Posted
3 days ago
Closes
Jun 17, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $192k
This role $145k
$122k most similar roles pay here $236k

This role pays less than 86% of similar roles. Most pay $162,500–$220,900 — the shaded band above. At the midpoint, this role pays about $145k versus about $192k 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 44 open roles on FindRole.

Listed pay typically runs $111,605–$131,300 across 41 roles with salary data.

Most-posted roles

View all roles at US Bank

At a glance

TL;DR · Integration and Automation Leader - Credit Risk Modeling

Join the Credit Risk Model Operations and Strategy team as a senior quantitative leader responsible for leading automation initiatives and redesigning key processes across the model lifecycle from SAS to Azure Databricks and Python. You will build robust data source connections, reusable code libraries, containerized environments, and testing pipelines while selecting and maintaining third-party tools. Key activities include enhancing model production, monitoring, implementation, reporting, and documentation capabilities for loan portfolio stress testing, allowance for credit losses, counterparty risk, and commercial risk rating scorecards. Proficiency in Python programming, Databricks, SQL, Git, AI/ML, and project management is essential, along with experience in system design and data science at regulated financial institutions.

What you'll do

  • Design and maintain reusable code libraries for model development and monitoring.
  • Lead the selection and onboarding of third-party tools and platforms for model operations.
  • Develop automated data pipelines using containerized environments like Docker and Kubernetes.
  • Implement orchestration tools to streamline workflows for reporting and documentation.
  • Partner with technology teams to migrate model infrastructure from SAS to Azure Databricks.
  • Train team members on automation tools, best practices, and new technologies.

What we're looking for

  • 10+ years of experience in quantitative fields or equivalent education and experience
  • Proficiency in object-oriented Python programming and Databricks for model lifecycle management
  • Experience with relational databases and SQL query optimization
  • Expertise in code management, version control using Git
  • Knowledge of AI/ML and generative AI approaches
  • Strong project management skills and ability to drive cross-team initiatives

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