U.S. Bank is seeking to solve real-world problems through quantitative research, development, and validation by hiring Quantitative Modeling Rotation Program Analysts.
Requirements
- Basic understanding of modeling and validation techniques in varying disciplines
- Strong programming skills such as C++, Python, R etc.
- Data compilation, programming skills, and qualitative analysis skills
- Statistical modeling background based on technical training or advanced education in a quantitative field such as Derivatives Pricing, Probability, Stochastic Calculus, Regressions, Machine learning etc.
- Knowledge of various regression techniques, parametric and non-parametric algorithms, times series analysis, or other statistical approaches, various model validation tests/methodologies
Responsibilities
- Get hands-on experience with project work creating, implementing, testing, documenting, and using models
- Rotate within our quantitative finance and risk groups (rotation options include: model risk management, treasury, credit risk, financial crimes, market risk, macroeconomics, and derivatives).
- Conduct model validation tests/methodologies and research to better understand modeling tools
- Participate in extra-curricular activities related to quantitative subjects
- Develop technical and business acumen through training, mentorship, and exposure to senior executives
- Build a supportive community of peers through a variety of cohort-strengthening activities such as social events, volunteer days, and development workshops
Other
- Master's or PhD degree in Statistics, Mathematics, Physics, Engineering, Financial Engineering/Mathematics, Economics, or other highly quantitative degrees
- Ability to start development program on July 13, 2026
- Strong written and verbal communication skills
- Ability to think and work independently within a professional setting
- Strong analytical, problem solving, and critical thinking skills
- Highly organized and motivated; ability to manage and prioritize multiple tasks and deadlines simultaneously
