The Forecasting and Capital Solutions team is a new group within the Office of the CFO responsible for the execution of a cohesive end to end analytic strategy across the firm’s $2.5 trillion dollar balance sheet by forecasting, stress testing, and utilizing bank capital analytic tools with the goal of refining and growing JPMorgan Chase’s suite of financial management capabilities.
We are searching for individuals with demonstrated Data Science tool execution experience to work on our next generation of forecasting and analytical tooling, with skills in one of the following areas, and willingness to learn a minimum of the others:
We work with every Line of Business, partnering with Finance, Risk and Technology teams to understand the business and user needs and collaboratively design tactical solutions. Our partners include Retail Banking (Credit Cards, Mortgage, Auto Loans, Deposits), Investment Banking, Asset Management, and the Chief Investment Office.
More specifically, this role requires the candidate to:
Knowledge of Machine Learning and some typical stacks for machine learning, e.g., scalable implementations of boosting, Tensorflow, MXNet, MLlib, scikit-learn, tooling in R's MachineLearning task view
Please note that J.P. Morgan will not accept unsolicited approaches or speculative CVs, nor will J.P. Morgan be responsible for any related fees, from Third Party Firms who are not preferred suppliers.
The firm invites all interested and qualified candidates to apply for employment opportunities.
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