Senior Quantitative Model Analyst - Wholesale Modeling

U.S. Bank • Minneapolis, MN

2d • Onsite

About The Position

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One. Job Description NOTE: This position is not eligible for current or future visa sponsorship. We are seeking a motivated individual contributor to support our Model Development & Decision Science (MDDS) team within Credit Risk Administration (CRA). This role will assist with the development, maintenance, and monitoring of expected loss forecasting models for our Commercial & Industrial portfolio in support of CECL, CCAR, and related internal risk management needs. About the CRA Team We are a collaborative team that supports the bank’s credit risk management through a focus on Customer, Process, Talent, and Data. Vision - We use data and analytics to improve credit risk decisions and support our customers. Mission - We deliver timely, accurate, and well-documented analytics that help protect stakeholders and inform key credit risk decisions. Values - We work with integrity, communicate clearly, collaborate well, and continuously learn. About the Role In this role, you will support model development work for Commercial & Industrial credit risk by helping prepare data, run analyses, and document results. You will partner with teammates and stakeholders in credit portfolio risk management, finance, model validation, and audit by providing clear summaries, well-organized materials, and reproducible code. This position is well-suited for someone who enjoys quantitative problem solving and wants to grow in model development within a regulated environment.

Requirements

• Experience supporting quantitative analysis and basic predictive modeling; ability to explain results clearly to technical and non-technical partners.
• Working knowledge of common analytics tools (e.g., Python/R/SAS, SQL) and comfort learning new systems and processes.
• Strong attention to detail and ability to execute well-defined tasks in a controlled environment, with appropriate escalation when issues arise.
• A collaborative, customer-focused mindset and willingness to learn credit risk concepts and governance expectations.
• Bachelor’s degree in a quantitative field, and 10 or more years of relevant experience OR - MA/MS in a quantitative field, and six or more years of related experience OR - PhD in a quantitative field, and five or more years of related experience

Nice To Haves

• Master or Ph.D degree in a quantitative or related field (e.g., economics, finance, mathematics, statistics, engineering, computer science) or equivalent practical experience.
• 5+ 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 (e.g., Python, R, SAS, SQL) and ability to learn additional tools as needed.
• Clear written and verbal communication skills, including the ability to document work and summarize results.
• Comfort working with defined controls and review processes (e.g., 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 effectively with partners across risk, finance, validation, and technology.
• Ability to build strong relationships with a wide range of individuals from risk, finance, model validation, technology, and regulators
• Strong analytical and problem solving skills, coupled with thoroughness and attention to detail
• Ability to prioritize work, meet deadlines, work under pressure and independently while balancing multiple priorities in a dynamic and complex environment
• Strong analytical, organizational, problem-solving, and project-management skills.
• Experience working with moderately large datasets and applying standard statistical techniques (e.g., regression, time series basics) is a plus.
• Familiarity with credit risk concepts (e.g., probability of default, loss given default) or exposure to model governance/validation processes is a plus.
• Comfort using Microsoft Excel and PowerPoint to summarize results and create clear exhibits.
• Experience writing clean, well-documented code in Python, R, SAS, or SQL.
• Basic automation or scripting exposure (e.g., 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 (e.g., using Git) is a plus.
• Exposure to cloud-based analytics environments (e.g., AWS or Azure) is helpful but not required.
• Interest in learning new analytics techniques and tools as the team evolves.
• Experience using standard Microsoft tools (Excel, PowerPoint, Word) to document and communicate analysis.
• Exposure to basic data visualization tools (e.g., Power BI or similar) is a plus.

Responsibilities

• Model development: design model development plan including model design, model methodology, model selection, model testing, benchmarking, and documentation under guidance of senior model developers.
• Data preparation and analysis: compile datasets, perform quality checks, and run standard exploratory analysis to support model development and monitoring.
• Partner with business and risk partners to understand data definitions and document changes in portfolio attributes or reporting needs.
• Monitoring and reporting: help prepare routine performance metrics and summaries; flag data or performance issues for follow-up.
• Documentation support: assist with preparing exhibits, tables, and written summaries used in governance, validation, and regulatory-related materials.
• Process improvement: identify opportunities to streamline data pulls, reporting, and repeatable analyses using existing tools and team guidance. You may collaborate with onshore and offshore partners to complete repeatable data and reporting tasks, following established procedures and quality checks.

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from 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 worked, up to 80 hours per calendar year unless otherwise provided by law

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees