U.S. Bank
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 strong, decisive, and results-oriented quantitative analyst to join our Quantitative Finance Forecast & Production ( QFFP ) team within U.S. Bank’s Corporate Treasury Division. In this role, the successful candidate will lead initiatives related to model implementation and infrastructure development, supporting key decision-making processes across Corporate Treasury. Key responsibilities include the research, design, deployment, and maintenance of an efficient forecasting platform, along with the implementation and operationalization of advanced statistical models to support balance sheet forecasting and risk analytics. About QFFP QFFP is a team within Corporate Treasury in the CFO organization responsible for producing forecasts that are used in capital, liquidity, and interest rate risk measurement, as well as baseline financial planning. QFFP leverages proprietary quantitative methods and systems to simulate and forecast comprehensive balance sheet and income statement metrics under a wide array of hypothetical scenarios. The team regularly partners with other strategy and risk management groups, such as Asset Liability Management and Capital & Liquidity Risk Management, as well as the Finance Data team. Core Competencies Experience leading quantitative teams, strong understanding of predictive modeling techniques, and familiarity with balance sheet data at large regulated financial institutions. Strong technology background including fundamental software engineering principles, automation tools, cloud-based tools and infrastructure, database systems, and dashboard/visualization tools. Exceptional communication skills and ability to drive transformation initiatives that span multiple teams and stakeholders. A mindset for curiosity, collaboration, customer centricity, and risk management. 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's Degree or PhD in a quantitative field such as quantitative finance, engineering, data science, mathematics, or statistics. 4 or more years of experience in a leading role in model development/implementation, software engineering, or related area. Strong familiarity with balance sheet modeling and cash flow forecasting. Deep understanding of banking, financial metrics, and asset & liability management. Knowledge of banking regulation and requirements for stress testing. Experience working with QRM. Excellent executive presence and verbal and written communication skills. Ability to build strong relationships with a wide range of individuals from finance, risk, 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 large datasets and building or validating advanced statistical models (including regression and economic factor models) Extensive programming experience in Python, familiar with profiling and performance optimization techniques. Experience with MS Word, Excel, and PowerPoint. Relational databases, SQL query optimization. Code management and version control using Git. Cloud-based solution deployment (AWS or Azure) and containerization/orchestration tools (e.g. Docker, Kubernetes). Al/ML and GenAI approaches. Microsoft Power Automate/ Power Apps. PowerBI or other visualization dashboards. 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 accom