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Consumer & Community Bank Finance, Treasury – Finance Modeling Internship – Columbus, OH

Req #: 170122191
Location: Columbus, OH, US
Job Category: Accounting/Finance/Audit/Risk
Job Description:
We are an intellectually diverse team of economists, statisticians, and other analytics professionals, focused on statistical modeling within the Treasury group of Consumer and Community Banking, the retail banking arm of JPMorgan Chase & Co. The team answers complex and unique questions, utilizing cutting edge analytical techniques and leveraging one of the world’s largest repositories of consumer data. We work closely with our partners throughout JPMorgan Chase to assess and execute critical business decisions.
The individual hired for this position will build models to answer questions and create forecasts for groups across the Finance organization at JPMorgan Chase.  Typical duties for this position include:
  • Building econometric models for deposits, revenue, or other business drivers
  • Modeling regulatory requirements, including stress testing (CCAR/DFAST)
  • Performing analysis to answer immediate business questions
  • Identifying data anomalies
  • Communicating results across audiences throughout JPMorgan Chase
Sample projects include:
  • Building budget and regulatory models to predict deposit account closure rates
  • Forecasting the performance of branches or bankers to optimize the branch network and staffing
  • Creating price elasticity models to optimize deposit and loan pricing
This position is in Columbus, OH, a strategic location for JPMorgan Chase’s corporate growth strategy.  Capital of Ohio and home to The Ohio State University, Columbus is known for its economic diversity and stability, highly educated population, and low cost of living.


We are looking for analytics professionals that possess:
  • Exceptional unstructured problem solving skills
  • Outstanding communications skills
  • Professional maturity and demonstrated leadership ability
  • Passion for analytics
  • Technical proficiency
Internship candidates should have passed qualifying exams on the way to a doctoral degree in a quantitative field of study, with a sound foundation in one or more of the following analytical disciplines:
  • Linear and non-linear statistical modeling
  • Time series and forecasting
  • Panel (longitudinal) data analysis
  • Data manipulation and management
  • Non-parametric methods
  • Statistical programming in R, Python, or equivalent
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