Description

JPMorgan Private Banking JP Morgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of more than $2 trillion and operations in more than 60 countries. We serve millions of U.S. consumers and many of the world's most prominent corporate, institutional and government clients. We are a leader in investment banking, financial services for consumers, small business and commercial banking, financial transaction processing, asset management and private equity. J.P. Morgan is a global leader in asset and wealth management services. We serve four distinct client groups through three businesses: institutions and retail clients through J.P. Morgan Asset Management; ultra high net worth clients through the Private Bank; and high net worth clients through Private Wealth Management. With assets under supervision of $1.7 trillion and assets under management of $1.2 trillion, we are one of the largest asset and wealth managers in the world. J.P. Morgan Private Banking, which includes both the Ultra High Net Worth and High Net Worth businesses, offers individuals and families personalized, comprehensive financial solutions that integrate sophisticated investment management, capital markets, trust and banking capabilities. We have more than 1,800 client advisors in 120 offices in 11 countries and 25 states. Matlab Intern, Investment Strategy Group The intern will help the J.P. Morgan Private Bank Economics team develop a plotting interface and supporting statistical programs using Matlab. Upon completion, this new interface will allow the economics team to rapidly compile and visualize data and analysis from all of its key vendors on one, integrated platform. A mastery of basic statistics including regression, correlation, interpolation, and filtering analysis is required. Strong programming experience in Matlab is also essential. Successful interns will have significant experience writing Matlab programs and functions that allow for variable input-output, leverage available Matlab toolboxes (Statistics, Datafeed) and properly handle missing observations in an efficient way.