JPMorgan Chase CCB - Risk-Fraud Data Scientist/Modeler-Text Mining-VP in Columbus, Ohio
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) s erves 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 Modeling Data Scientist will be a key individual contributor on the Fraud Modeling team that is responsible for developing and implementing best-in-class fraud prevention and detection models and analytical tools. The CCB Fraud Modeling team is an analytical center of excellence to all fraud risk managers and operations across the bank. The team provides diverse models and analytical tools used to identify potentially fraudulent transactions across different lines of business (card, retail, auto, merchant services).
In this role, you will be the analytical expert for identifying and retooling suitable machine learning algorithms that can enhance the fraud risk ranking of particular transactions and/or applications for new products. This includes a balance of feature engineering, feature selection, and developing and training machine learning algorithms using cutting edge technology to extract predictive models/patterns from data gathered for hundreds of millions transactions. Your expertise and insights will help us effectively utilize big data platforms, data assets, and analytical capabilities to control fraud loss and improve customer experience.
Particular to this role, we are seeking a motivated individual that specializes in natural language processing (NLP) and analyzing unstructured text. You will be responsible for analyzing unstructured texts collected through various customer interaction points to find patterns and features and use them to develop machine learning models that can be used to improve the efficiency of fraudulent activity detection.
Master's degree in Mathematics, Statistics, Economics, Computer Science, Operational Research, Physics, and other related quantitative fields
1-3 experience in developing commercial applications for text mining and natural language processing
1-3 years’ experience in open source programming languages for large scale data analysis such as Python / Scala / Java
Experience in developing models using some (at least 3) of the following machine learning and optimization techniques like CNN, RNN, SVM, Reinforcement Learning, Markov Process for a commercial purpose
Ph.D. Mathematics, Statistics, Economics, Computer Science, Operational Research, Physics, or related field
Secured patents in area of speech recognition and / or speaker identification
Academic papers published in the area of machine learning in the top machine learning journals
Experience with implementing scalable machine learning/data mining algorithms making use of distributed/parallel processing
JPMorgan Chase is an equal opportunity and affirmative action employer Disability/Veteran.