Make your mark protecting customers by turning complex analytics into fraud strategy, with strong growth and mobility prospects.
As a Quantitative Analytics Associate within the Fraud Prevention Optimization Strategy team, you reduce fraud losses and operating expenses while balancing customer impact by optimizing business processes and decisioning. You deliver complex analyses paired with business insight, collaborate with cross-functional partners, and present conclusions succinctly to managers and executives. You leverage advanced analytics and tools such as large language models to drive sustainable, scalable business improvements.
Job Responsibilities:
Interpret complex data to define problem statements and deliver concise conclusions on risk dynamics, trends, and opportunities
Apply advanced analytical and mathematical techniques to solve complex business problems
Develop, communicate, implement, and manage fraud strategies to reduce fraud-related losses and improve customer experience across the credit card fraud lifecycle
Identify key risk indicators, define and enhance key metrics and reporting, and uncover new areas of analytic focus to challenge current business practices
Provide data insights and performance updates to business partners
Collaborate with cross-functional partners to solve key business challenges
Support critical projects with explicit, concise verbal and written communication across functions and levels
Champion the use of contemporary technology and tools, such as large language models, to drive value at scale
Required qualifications, skills, and capabilities:
Bachelor's degree in engineering, statistics, mathematics, or another quantitative field, or 3+ years of risk management or other quantitative experience
Proficiency in Python, SAS, and SQL
Ability to query large datasets and translate results into actionable recommendations
Strong analytical and problem-solving skills
Experience delivering