Quantitative Model Analyst - Wholesale Modeling

Motivated individual contributor to support the Model Development & Decision Science (MDDS) team within Credit Risk Administration (CRA). The role assists with the development, maintenance, and monitoring of expected loss forecasting models for the Commercial & Industrial portfolio in support of CECL, CCAR, and related internal risk management needs. Location expectation: works from a U.S. Bank location three (3) or more days per week.

Responsibilities

Support model development work for Commercial & Industrial credit risk by helping prepare data, run analyses, and document results; 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; 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

Requirements

Bachelor's degree in a quantitative field and eight or more years of relevant experience, OR MA/MS in a quantitative field and five or more years of related experience, OR PhD in a quantitative field and four or more years of related experience; 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); Comfort learning new systems and processes; Strong attention to detail and ability to execute well-defined tasks in a controlled environment; Collaborative, customer-focused mindset and willingness to learn credit risk concepts and governance expectations; Proficiency with at least one programming or analytics tool (e.g., Python, R, SAS, SQL); Clear written and verbal communication skills; Comfort working with defined controls and review processes; Ability to manage multiple tasks and meet deadlines; Strong interpersonal skills; Strong analytical and problem-solving skills

Nice to have

Master or Ph.D degree in a quantitative or related field or equivalent practical experience; 4+ years of experience in analytics, reporting, statistical analysis, or related quantitative work; Financial services experience; Experience working with moderately large datasets and applying standard statistical techniques (e.g., regression, time series basics); Familiarity with credit risk concepts (e.g., probability of default, loss given default) or exposure to model governance/validation processes; Comfort using Microsoft Excel and PowerPoint; Experience writing clean, well-documented code in Python, R, SAS, or SQL; Basic automation or scripting exposure; Familiarity with SQL and relational databases; Familiarity with Git; Exposure to cloud-based analytics environments (AWS or Azure); Exposure to data visualization tools (e.g., Power BI)

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 (two to five weeks depending on salary grade and tenure); Up to 11 paid holiday opportunities; Adoption assistance; Sick and Safe Leave accruals