Join the team that is responsible for measuring the effectiveness of and driving Chase’s Consumer Bank strategies across marketing, sales, distribution, pricing, and customer analytics. 

As a Data Science Senior Associate, within the Customer Analytics team, you will be supporting the Affluent Customer Analytics line of business where you will be a strategic thinker with the ability to focus on business goals, and will be excellent at solving unstructured problems independently.  

Job Responsibilities:

Develop reporting and conduct complex analyses in partnership with Consumer Bank product and finance teams, including product and servicing channel performance analyses, client engagement and attrition analyses, customer segmentation work, and more.Consult with business partners on analytical needs and make strategy recommendations.Solve unstructured business problems and develop deep dive analyses of customer behavior using a variety of analytic, statistical, and machine learning tools and techniques.Break down complex analytic results and concepts into relevant and digestible takeaways, and present them to stakeholders and senior management.Continuously develop skills to provide best-in-class analytics to the business.

Required qualifications, capabilities, and skills:

Master’s degree in a quantitative discipline or a Bachelor’s degree and 3+ years of experience in a quantitative discipline (Data Science/Analytics, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or related fields).3+ years of experience in applying statistical and machine learning methods to real-world problems.3+ years of experience with SQL and at least one of the following analytical tools: SAS, Python, and/or RExperience with visualization techniques for data analysis and presentations Superior written, oral communication, and presentation skills with experience communicating concisely and effectively with all levels of management and partners.

Preferred qualifications, capabilities, and skills:

Python preferredTableau preferred