JPMorgan Senior Quantitative Analytics Associate 

United States, Delaware, Wilmington 

52362335

Job responsibilities:

• Interpret big and complex data to formulate problem statements and concise conclusions regarding underlying risk dynamics, trends, and opportunities.
• Manage, develop, communicate, and implement optimal fraud strategies (including rules, cutoffs, policies, operational flows, etc.) to protect the bank from fraud-related losses and improve customer experience at the Point of Sale.
• Identify key risk indicators and metrics, develop key metrics, enhance reporting, and identify new areas of analytic focus to better capture fraud.
• Provide subject matter expertise on strategy implementation/testing and initiatives related to the improvement of risk mitigation processes and infrastructure.
• Collaborate with cross-functional partners to understand and address key business challenges.
• Identify business opportunities by performing well-thought analysis—data mining, ensuring data integrity, synthesizing, and communicating findings to senior management.
• Assist team efforts in the critical development of new fraud pattern or spending pattern detection tools while providing clear and concise oral and written communication across various functions and levels, inclusive of Operations, IT, and Risk Management.

Required qualifications, capabilities, and skills:

• BS degree in a quantitative field
• 4 years of experience in an analytical role with proven ability of problem-solving abilities
• Background in statistics, mathematics, or other quantitative field
• Advanced understanding of Python, SAS, and SQL
• Query large amounts of data and transform the raw data into actionable management information
• Experience delivering recommendations to management
• Self-starter with ability to drive for resolution
• Strong communication and interpersonal skills with ability to interact with individuals across departments/functions and with senior-level executives

Preferred qualifications, capabilities, and skills:

• MS degree in Industrial Engineering or other Engineering discipline
• Experience working in Fraud, either in banking or non-banking
• Experience working in AML