Join our dynamic team as a Quantitative Analytics Associate on the Consumer and Community Banking Fraud Prevention Optimization Strategy team. This role offers a chance to reduce fraud costs and enhance customer experience through complex analyses and collaboration. You'll engage with cross-functional partners, presenting insights to promote impactful business improvements while protecting the bank.

 

Job Summary

As a Quantitative Analytics Associate on our Consumer and Community Banking (CCB) Fraud Prevention Optimization Strategy team, you will focus on reducing the cost of fraud through complex analyses combined with business insights and collaboration. You will work towards reducing losses and operating expenses while balancing customer impact by optimizing business processes and decision-making. You will frequently interact and communicate with cross-functional partners and present complex analysis succinctly to managers and executives. This role provides an opportunity to be part of a dynamic team that is instrumental in protecting the bank by leveraging complex analytics and new tools like large language models to deliver sustainable, impactful business improvements.

Job Responsibilities 

Interpret and analyze complex data to formulate problem statement, provide concise conclusions regarding underlying risk dynamics, trends, and opportunities. Use advanced analytical & 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 credit card fraud lifecycle.  Identify key risk indicators, develop key metrics, enhance reporting, and identify new areas of analytic focus to constantly 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 the critical projects while providing clear/concise oral and written communication across various functions and levels. Champion the usage of latest technology and tools, such as large language models, to drive value at scale across business organizations.

 

Required qualifications, capabilities, and skills 

Bachelor’s degree in a quantitative field or 3 years risk management or other quantitative experience Background in Engineering, statistics, mathematics, or another quantitative field  Advanced understanding of Python, SAS, and SQL Query large amounts of data and transform into actionable recommendations. Strong analytical and problem-solving abilities Experience delivering recommendations to leadership. Self-starter with ability to execute quickly and effectively. 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 a quantitative field or 2 or more years 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