Join the Finance Decision Optimization team, a group of product, analytics, and engineering experts, who support the development of predictive models used to drive strategic decisions across Consumer and Community Banking Finance.

As a Quant Analytics Senior Associate, within the Finance Decision and Deposits Area team, you will use multi-faceted analytics to support the end-to-end development of the deposit pricing model, which is a framework used to help support deposit pricing decision making.

Job Responsibilities:

Partner with the business modeling team to develop and refine statistical models while continuously evaluating their performance and effectiveness. Execute model forecasts and socialize results to business partners and stakeholders to help drive pricing strategy.Translate business demands to technical requirement documents and collaborate with technology teams. Work closely with end-users and data product owners to build datasets for model training and serving.Independently design, develop, and optimize complex SQL queries and Python scripts to support data validation, exploration, and integration with existing systems and codebases.Effectively manage multiple tasks and priorities in a fast-paced environment while maintaining responsiveness to ad-hoc requests. 

Required qualification, capabilities, and skills:

Strong problem solver with excellent analytical, critical thinking, communication, organizational, and technical skills.5+ years of experience at a financial institution or consulting firm in one or a combination of the following areas: corporate finance, banking, treasury, data analytics, or quantitative modeling. Able to communicate effectively with a variety of technical peers including data engineering and quantitative modeling teams.

Preferred qualification, capabilities, and skills:

Proficiency in business analytics tools or programming languages (e.g. SQL, SAS, Python, R). Experience with Databricks, Streamlit, and AWS Cloud environments is a plus.Preference to those with experience dealing with large scale data projects.