Lead Treasury Quantitative Analytics (VP)

Wells Fargo•New York, NY

1d•Hybrid

About The Position

Wells Fargo is seeking a Quantitative Analytics Vice President to conduct analysis, development, and implementation of the bank stress and forecast models within Liquidity Management. The candidate should be particularly adept at Python model implementation and integrated high-performance dynamic modeling. Treasury at Wells Fargo is a dynamic team that is responsible for managing Wells Fargo's balance sheet including capital, liquidity, funding, and interest rate risk management. Treasury seeks to ensure Wells Fargo always maintains sufficient capital and liquidity resources to support growth in the Company's businesses, while also ensuring a satisfactory financial cushion exists to protect against unforeseen stresses in the economic environment or the Company's operations. Treasury also provides regulators, senior leaders, and the Board of Directors with key information to support risk management, financial performance management, and strategic planning.

Requirements

5+ years of Quantitative Analytical experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Nice To Haves

Knowledge of bank products across Retail and Wholesale businesses, including Deposits, Secured Financing, and Prime Brokerage activities
Design, write and maintain high-quality code in Python, C++, or similar languages; querying via SQL or with data lake structures; familiarity with interface wrappers preferable; interacting with large data environments and building components within a larger application
A strong sense of ownership and self-starter with attention to detail
Ability to deliver multiple concurrent projects or large-scale individual projects
Polished communication skills and ability to communicate complex ideas in a simple, straightforward manner to executive management
Thrives in a large organization, collaborating with many teams

Responsibilities

Build best in class models and tools that directly inform the Liquidity risk position of the firm
Self-start and own initiatives including creation, implementation, documentation, validation, and defense of statistical theory
Leverage technology to apply mathematical and statistical techniques that represent financial product behaviors under different scenarios
Devise creative and novel solutions to methodology challenges or in response to market events
Guide technology partners in the needs and future designs of our computational backbone
Document methodology changes and updates through technology and governance
Present results of analysis and strategies to the management of the firm