Quantitative Analytics Associate - Fraud Prevention Optimization Strategy

About the role

Join the Consumer and Community Banking (CCB) Fraud Prevention Optimization Strategy team as a Quantitative Analytics Associate to reduce fraud costs and improve customer experience. This role offers a breadth of experiences, learnings, and connections to support your growth and development. You will be part of a dynamic team instrumental in protecting the bank by leveraging complex analytics and new tools like large language models to deliver sustainable business improvements.

Responsibilities

• Interpret and analyze complex data to formulate problem statements, provide concise conclusions regarding underlying risk dynamics, trends, and opportunities.
• Use advanced analytical and mathematical techniques to solve complex business problems.
• Manage, develop, communicate, and implement optimal fraud strategies to reduce fraud-related losses and improve customer experience across the credit card fraud lifecycle.
• Identify key risk indicators, develop key metrics, enhance reporting, and identify new areas of analytic focus to challenge current business practices.
• Provide key data insights and performance to business partners.
• Collaborate with cross-functional partners to solve key business challenges.
• Assist team efforts in critical projects while providing clear and concise oral and written communication across various functions and levels.
• Champion the usage of the latest technology and tools, such as large language models, to drive value at scale across business organizations.

Requirements

• Bachelor’s degree in a quantitative field or 3 years of risk management or other quantitative experience.
• Background in Engineering, statistics, mathematics, or another quantitative field.
• Advanced understanding of Python, SAS, and SQL.
• Ability to query large amounts of data and transform it into actionable recommendations.
• Strong analytical and problem-solving abilities.
• Experience delivering recommendations to leadership.
• Self-starter with the ability to execute quickly and effectively.
• Strong communication and interpersonal skills with the ability to interact with individuals across departments/functions and with senior-level executives.

Preferred Qualifications

• MS degree in a quantitative field or 4 or more years of risk management or other quantitative experience.
• Hands-on knowledge of AWS and Snowflake.
• Advanced analytical techniques like Machine Learning, Large Language Model Prompting, or Natural Language Processing.

About the Team

Our Consumer & Community Banking division serves Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans, and payment processing. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses disciplines from data governance and strategy to reporting, data science, and machine learning, with a strong partnership with Technology to provide cutting-edge data and analytics infrastructure.