Quantitative Model Analyst - Wholesale Modeling

U.S. Bank; Brea (CA); On-site; USD 110,000 - 165,000; Full time

Benefits offered by this job

Healthcare

401(k) plan

Life insurance

Disability insurance

Parental leave

Job summary

U.S. Bank is seeking a motivated individual contributor to support its Model Development & Decision Science team within Credit Risk Administration.

The role focuses on developing, maintaining, and monitoring expected loss forecasting models for the Commercial & Industrial portfolio to support CECL, CCAR, and related risk management needs. You will partner with teammates across credit portfolio risk management, finance, model validation, and audit, delivering clear summaries, organized materials,

Qualifications

• Bachelor's or higher in a quantitative field with extensive relevant experience
• Experience supporting model development in credit risk or related domains
• Ability to communicate results clearly to technical and non-technical partners
• Familiarity with governance, validation, and regulatory processes

Responsibilities

• Assist with data preparation, analysis, and documentation for CECL/CCAR-related models.
• Support model development, testing, benchmarking, and documentation under senior guidance.
• Collaborate with risk, finance, validation, and audit teams to ensure reproducible analyses.

Skills

Model development

Data preparation

Analytical thinking

Communication

Education

Bachelor's degree

MA/MS in quantitative field

PhD in quantitative field

Tools

Python

R

SQL

SAS

Job description

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

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.

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.

Key Activities

• 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.

Core Competencies

• 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.

Basic Qualifications

• 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

Preferred Skills/Experience

• Master or Ph.D degree in a quantitative or related field (e.g., economics, finance, mathematics, statistics, engineering, computer science) or equivalent practical experience.
• 4 + 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, model validation, 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.

Preferred Skills

• 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.

LOCATION EXPECTATIONS:

This role requires working from a U.S. Bank Location three (3) or more days per week.

If there's anything we can do to accommodate a disability during any portion of the application or hiring process, please refer to our disability accommodations for applicants.

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‑