Senior Quant Analytics Associate - Fraud Risk

Job Description

If you are passionate about leveraging advanced analytics and AI to combat fraud and drive business value, we encourage you to apply!

As a Senior Quantitative Analytics Associate in our Fraud Risk team, you will help prevent plastics fraud through advanced, data-driven analysis. You'll gain a comprehensive understanding of the point-of-sale transaction lifecycle and deliver timely, efficient, and tailored solutions. You will collaborate with cross-business partners to leverage advanced analytics for fraud/scam prevention, dispute and claim management, and optimization of risk/reward tradeoffs (losses/OpEx/customer experience), with the goal of driving positive business outcomes.

• Analyze large datasets to detect patterns, trends, and anomalies indicative of fraudulent activity.
• Build, develop, and maintain reporting and data automation systems to communicate insights to leadership for strategic decision-making.
• Enhance internal analytical techniques and introduce best practices to improve key business metrics.
• Work independently and collaboratively with cross-functional partners, from problem identification to data analysis and delivering actionable recommendations.
• Develop and implement GenAI and Agentic AI solutions using Python to automate and optimize decision-making processes.
• Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to improve decision-making and workflow efficiency across fraud operations and customer experience.
• Design and demonstrate proof‑of‑concepts (POCs) for extracting insights from structured and unstructured data using advanced analytics; build and iterate on prototype solutions.
• Stay current with the latest research in LLM, ML, and data science, and leverage emerging techniques for ongoing enhancement.

• Advanced degree in a quantitative discipline (e.g., Computer Science, Mathematics, Operations Research, Data Science).
• 3+ years of experience in Risk Management or any quantitative field
• Hands‑on experience with SQL, Python, and Alteryx.
• Strong understanding of the foundational principles and practical implementation of machine learning algorithms for anomaly detection, including clustering, classification, neural networks, distance‑based, and time series methods.
• Experience creating generative AI solutions using LLM prompt engineering and Retrieval Augmented Generation (RAG).
• Experience with evaluation metrics for ML and generative AI.
• Demonstrated ability to communicate complex concepts and results to both technical and business audiences.

• Hands‑on experience with behavioral and transactional analytics tools and techniques.
• Familiarity with model explainability and self‑validation techniques.
• Preferred experience supporting more than one CCB Operations Function/Line of Business.

This role is not eligible for visa sponsorship. This role is 5 days a week full time in office.

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility.

These benefits include comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be…