Quantitative Analytics Associate - Fraud Prevention Optimization Strategy

Are you interested in joining a dynamic team? Become a Quantitative Analytics Associate on our Consumer and Community Banking (CCB) Fraud Prevention Optimization Strategy team to reduce the cost of fraud and improve customer experience. The breadth of experiences, learnings, and connections in this role will enable your growth and development. To excel, you'll be highly motivated, highly analytical, extremely detail‑oriented, and an exceptional problem solver who takes pride in being part of an organization that owns customer issues from beginning to end and delivers accurate, timely solutions. As a Quant Analytics Associate in our Fraud Prevention Optimization team you will focus on reducing the cost of fraud through complex analyses combined with business insights and collaboration. Your objective is to reduce losses and/or operating expenses while balancing customer impact through 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. You will be provided 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, hard‑hitting business improvements. Job 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 constantly challenge current business practices. Provide key data insights and performance metrics 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 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 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, Capabilities, And Skills 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 such as machine learning, large language model prompting, or natural language processing will be an added advantage. 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. #J-18808-Ljbffr JPMorganChase