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# Data Scientist

- **Company:** U.S. Bank, National Association
- **Location:** Earth City, MO, United States
- **Experience:** Expert
- **Salary:** $111,605.0 - $131,300.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Data Governance, Extract Transform Load (ETL), Data Visualization, Data Warehousing, Machine Learning, Meta-Data Management, Feature Engineering, Large Language Models, Prompt Engineering, Generative AI, AI Platforms, Information Technology, Machine Learning Operations, Physical Data Models, Data Pipelines
- **Published:** July 14, 2026
- **Apply:** https://usbank.wd1.myworkdayjobs.com/US_Bank_Careers/job/Earth-City-MO/Data-Scientist_2026-0018812

## About the Role

Bachelor's degree in a quantitative field such as statistics, computer science, engineering or applied mathematics, or equivalent work experience

 - Six to eight years of relevant experience

Preferred Skills/Experience

*

 + Experience with Generative AI, Prompt Engineering, and LLM optimization.
 + Knowledge of Retrieval-Augmented Generation (RAG) frameworks.
 + Experience with Azure AI, Azure OpenAI, AWS AI Services, or related cloud AI platforms.
 + Experience with MLOps and model lifecycle management.
 + Financial Services or Mortgage industry experience.
 + Experience leading technical initiatives and mentoring team members.
 + Expertise in Machine Learning and Artificial Intelligence.
 + Experience working with LLMs and Generative AI technologies.
 + Strong collaboration and leadership skills.
 + Ability to adapt in a fast-paced, evolving environment.
 + Ownership mindset with a passion for innovation and continuous learning.

## Description

* Design and maintain conceptual, logical, and physical data models supporting mortgage origination, underwriting, servicing, and lending technology platforms.
 * Develop predictive and prescriptive analytics solutions utilizing machine learning, statistical modeling, and AI techniques.
 * Collaborate with engineering teams to build scalable data solutions across cloud, data warehouse, and ETL ecosystems.
 * Analyze large and complex datasets to identify business trends, operational efficiencies, customer behaviors, and risk indicators.
 * Define enterprise data standards, metadata management practices, and data governance processes.
 * Build data pipelines, feature engineering frameworks, and analytical datasets supporting reporting and advanced analytics use cases.
 * Partner with business stakeholders to translate lending and mortgage business requirements into scalable data models and actionable insights.
 * Develop dashboards, KPIs, data visualizations, and executive reporting solutions for operational and strategic decision-making.
 * Ensure data quality, integrity, lineage, and compliance with regulatory and security requirements.
 * Support modernization initiatives involving cloud platforms, real-time analytics, and enterprise data architecture.


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