JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with operations worldwide. The firm is a leader in investment banking, financial services for consumers and small business, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world's most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Information about JPMorgan Chase & Co. is available at http://www.jpmorganchase.com/.
Our Firmwide Risk Function is focused on cultivating a stronger, unified culture that embraces a sense of personal accountability for developing the highest corporate standards in governance and controls across the firm. Business priorities are built around the need to strengthen and guard the firm from the many risks we face, financial rigor, risk discipline, fostering a transparent culture and doing the right thing in every situation. We are equally focused on nurturing talent, respecting the diverse experiences that our team of Risk professionals bring and embracing an inclusive environment.
Chase Consumer & Community Banking (CCB) serves consumers and small businesses with a broad range of financial services, including personal banking, small business banking and lending, mortgages, credit cards, payments, auto finance and investment advice. Consumer & Community Banking Risk Management partners with each CCB sub-line of business to identify, assess, prioritize and remediate risk. Types of risk that occur in consumer businesses include fraud, reputation, operational, credit, market and regulatory, among others.
The CCB Risk Core Credit Card Modeler will be responsible for end-to-end management of complex model development, working with the model governance team on model review process as well as leading ad-hoc analytic projects on alternative modeling approaches to drive innovation and research new opportunities for revenue growth or risk mitigation. In this highly visible role, the successful candidate will be able to think like an analytic leader with overall business picture in mind and develop & communicate the business analytics and model statistics/insights to senior management.
Success in this role requires a strong foundation in predictive modeling and machine learning algorithms coupled with experience in working with large dataset. Prior experience in working with financial data is desirable. A successful candidate will be able to collaborate in a team environment and communicate his/her findings succinctly to senior leaders when needed.
. Your key responsibilities will include:
Develop or apply mathematical or statistical theory and methods to collect, organize, interpret, and summarize numerical data to discover useful information.
Analyze and interpret big data and its impact in both operational and financial areas following comprehensive risk principles and procedures.
Feature engineering and feature selection for traditional GLM models and machine learning models
Design, develop, implement and validate statistical models and / or machine learning algorithms for bank’s card risk, marketing and collection strategies.
Utilize graduate-level research and analytical skills to perform data extraction, sampling, and statistical analyses using logistic regression, multinomial regression, neural network, gradient boosting algorithms, multivariate analysis, discriminant analysis, principal components analysis, etc.
Conduct complex risk analysis to provide management with business insights, recommendations of strategies and business actions for profitable growth opportunities, consumer credit quality and behavior trends, desired risk/return relationships and portfolio performance.
Partner with business units in making strategic choices and investment decisions. Communicate opportunities, financial and process trade-offs from advanced statistical methods to senior leaders.