Quantitative Analytics Sr| Associate

Description for Internal Candidates Who We Are JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $2.7 trillion and 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. What it Means To Work Here Here, you'll feel welcomed and valued. Our clients, transactions, deals and projects are global so we work hard to create diverse, inclusive teams that support our business and each other.. What to Expect Chase Consumer & Community Banking (CCB) serves nearly 66 million consumers and 4 million small businesses with a broad range of financial services through our 137,000 employees The Point of Sale Fraud Strategy team within CCB Operations is an analytics team responsible for creating and maintaining the authorization strategy used for decisioning transactions while mitigating fraud risk across products like Credit Cards, Debit Cards, Commercial cards. The team manages authorization of 60 MM+ transactions daily translating into $1.5 trillion of annual credit and debit card sales and $0.5 billion fraud risk exposure to the bank across plastics The strategies leverage machine learning based fraud models, internal/external data sources , customer & merchant behavioral data along with statistical optimization techniques to help detect and prevent unauthorized fraudulent transactions across different third party loss types, protecting our customers and the firm while also creating best in class customer experience at the Point of Sale Primary Responsibilities: Own and manage fraud recovery risk mitigation strategies across credit card / debit card portfolios by synthesizing & analyzing complex transactional data and drawing concise conclusions regarding underlying risk dynamics, trends, and opportunities Assist team in managing critical machine learning & other score upgrades or refreshes that influence authorization strategies outcomes by working with internal / external modeling partners or associations like Visa / Mastercard Continue to enhance existing recovery strategy to ensure optimal outcomes across key portfolio segments while ensuring profitable return on investment goals Develop new model input variables, profiles and expand data footprint / pattern detection techniques & other capabilities to improve accuracy of recovery decisions across functions Partner effectively with Claims / Recovery to identify and execute data driven analytical strategy enhancements Ensure compliance with existing control structure while also driving