Fraud Prevention Data Analytics Associate

Fraud Prevention Strategy - Data Analytics Associate Make your mark protecting customers by turning complex analytics into fraud strategy, with strong growth and mobility opportunities. 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 clear, concise verbal and written communication across functions and levels Champion the use of modern 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 recommendations to leadership Self-starter with the ability to execute quickly and effectively Strong communication and interpersonal skills, with the ability to partner across departments and functions and with senior-level leaders Preferred qualifications, skills, and capabilities: Master’s degree in a quantitative field, or 4+ years of risk management or other quantitative experience Hands-on knowledge of Amazon Web Services and Snowflake Experience applying machine learning, large language model prompting, or natural language processing techniques JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Experience Level Mid Level