Senior Quantitative Model Analyst - Wholesale Modeling

U.S. Bank • Minneapolis, MN

5d • $148,495 - $174,700 • Hybrid

About The Position

U.S. Bank is seeking a motivated individual contributor to support its Model Development & Decision Science team within Credit Risk Administration. The role assists with developing, maintaining, and monitoring expected loss forecasting models for the Commercial & Industrial portfolio in support of CECL, CCAR, and related internal risk management needs.

The analyst supports model development by preparing data, conducting analyses, and documenting results. They work with teammates and stakeholders in credit portfolio risk management, finance, model validation, and audit, providing clear summaries, organized materials, and reproducible code. The role is suited to someone interested in quantitative problem solving and growing in model development within a regulated environment.

The position requires working from a U.S. Bank location three or more days per week. The salary range is $148,495 to $174,700, subject to variation based on the role's location.

Requirements

• Bachelor’s degree in a quantitative field and 10 or more years of relevant experience; or a master’s degree in a quantitative field and six or more years of related experience; or a Ph.D. in a quantitative field and five or more years of related experience.
• Experience supporting quantitative analysis and basic predictive modeling, with the ability to explain results clearly to technical and non-technical partners.
• Working knowledge of common analytics tools such as Python, R, SAS, or SQL, and comfort learning new systems and processes.
• Strong attention to detail and ability to execute well-defined tasks in a controlled environment, escalating issues appropriately.
• Collaborative, customer-focused mindset and willingness to learn credit risk concepts and governance expectations.

Nice To Haves

• Master’s or Ph.D. degree in a quantitative or related field, such as economics, finance, mathematics, statistics, engineering, or computer science, or equivalent practical experience.
• Five or more years of experience in analytics, reporting, statistical analysis, or related quantitative work; financial services experience is a plus.
• Proficiency with at least one programming or analytics tool, such as Python, R, SAS, or SQL, and ability to learn additional tools.
• Clear written and verbal communication skills, including documenting work and summarizing results.
• Comfort working with defined controls and review processes, such as peer review, documentation standards, and change management.
• Ability to manage multiple tasks, meet deadlines, and maintain quality in a fast-paced environment.
• Strong interpersonal skills and ability to work with partners across risk, finance, validation, and technology.
• Ability to build relationships with individuals from risk, finance, model validation, technology, and regulatory groups.
• Strong analytical, organizational, problem-solving, and project-management skills, as well as thoroughness and attention to detail.
• Ability to prioritize work, meet deadlines, work under pressure and independently, and balance multiple priorities in a dynamic environment.
• Experience with moderately large datasets and standard statistical techniques, such as regression and basic time series, is a plus.
• Familiarity with credit risk concepts, such as probability of default and loss given default, or exposure to model governance or validation processes, is a plus.
• Comfort using Microsoft Excel and PowerPoint to summarize results and create exhibits.
• Experience writing clean, well-documented code in Python, R, SAS, or SQL.
• Basic automation or scripting experience, such as simple batch jobs, scheduled tasks, or reusable notebooks, is a plus.
• Familiarity with SQL and relational databases for querying and validating data.
• Familiarity with basic version control concepts, such as Git, is a plus.
• Exposure to cloud analytics environments such as AWS or Azure is helpful but not required.
• Interest in learning new analytics techniques and tools as the team evolves.
• Experience using Microsoft Excel, PowerPoint, and Word to document and communicate analysis.
• Exposure to data visualization tools such as Power BI is a plus.

Responsibilities

• Support model development planning, including model design, methodology, selection, testing, benchmarking, and documentation under guidance of senior model developers.
• Compile datasets, perform quality checks, and conduct standard exploratory analyses to support model development and monitoring.
• Work with business and risk partners to understand data definitions and document changes in portfolio attributes or reporting needs.
• Help prepare routine performance metrics and summaries, and flag data or model performance issues for follow-up.
• Assist in preparing exhibits, tables, and written summaries for governance, validation, and regulatory-related materials.
• Identify opportunities to streamline data pulls, reporting, and repeatable analyses using existing tools and team guidance.
• Collaborate with onshore and offshore partners on repeatable data and reporting tasks, following established procedures and quality checks.

Benefits

• Healthcare coverage, including medical, dental, and vision
• Basic term and optional term life insurance
• Short-term and long-term disability coverage
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation of two to five weeks, depending on salary grade and tenure
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 hours worked, up to 80 hours per calendar year unless otherwise provided by law
• Incentive and recognition programs
• Equity stock purchase
• Pension

What This Job Offers

• Job Type: Full-time
• Career Level: Senior