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 U.S. Bank is seeking a full-time Quantitative Model Analyst (Multiple openings) in Reno, NV. The Quantitative Model Analyst (multiple openings) is responsible for the support and development of SA-CCR/SA-CVA (Credit Valuation Adjustment Risk) and XVA (Valuation Adjustment) models and analytics tools, derivatives pricing, and hedging operations with a specific focus on complex quantitative methods employed in the valuation and associated risk mitigation. This position contributes to the development, testing and documentation of such mathematical tools and conducts optimal hedge analysis to support the desk. Specific duties include: (1) financial engineering focusing on derivatives; (2) implementing option pricing methodology and models covering the following asset classes: fixed income, FX, equity and credit (credit index options) as well as numerical implementation and calibration of said derivatives/models in an object-oriented framework (3) Pricing multiple asset classes individually and within hybrid models for fixed income, foreign exchange, equity, and credit; (4) establishing correlations between diverse model parameters, predicting financial model parameters using the trained fTT mapping, and testing the predictions against market implied volatilities; (5) object-oriented implementation of adjoint algorithmic differentiation for derivatives pricing and greeks; (6) utilizing efficiency techniques used in complex derivatives valuation, in particular variance reduction techniques, tensor methods and nonlinear optimization; (7) writing object-oriented C++, C#, and Java code within visual studio and Python; and (8) implementing the Crank-Nicolson method for partial differential equations and nonlinear optimization algorithms including Levenberg-Marquart.