Senior Product Manager - Fraud

Mercury•San Francisco, NY

18h

About The Position

Mercury is seeking a Senior Product Manager for Fraud to build products that balance customer experience with fraud prevention. The role involves developing a deep understanding of customers, their accounts, and money movement products to create systems that protect customers and Mercury from fraud. The Product Manager will work cross-functionally on products for end users and internal risk teams, helping provide a seamless and safe banking experience. The position will lead efforts to redefine how risk friction is used, measured, and optimized. Mercury is a fintech company, not an FDIC-insured bank. Banking services are provided through Choice Financial Group and Column N.A., Members FDIC.

Requirements

At least 7 years of relevant product management experience, including experience within fraud or risk in banking or fintech environments.
Deep customer empathy and understanding of how risk friction affects user experience, growth, and retention.
Experience working with complex automated decisioning systems, rules, machine learning models, and real-time data pipelines.
Proficiency with analytics and the ability to understand performance of rules and machine learning models, evaluate precision/recall trade-offs, and translate insights into actionable priorities.
Strong track record of cross-functional leadership, particularly in navigating trade-offs between risk, compliance, and customer experience priorities.
Exceptional communication skills and ability to translate complex risk concepts into actionable product strategies.
Comfort with ambiguity and ability to make balanced decisions with imperfect information.

Responsibilities

Shape the strategy and roadmap for fraud prevention across areas such as account integrity, money movement, and the decisions, controls, and experiences that protect customers.
Design and execute the strategic vision to mitigate fraud and improve risk experience, including holds, limit structures, step-up verification, and related friction points.
Craft user journeys that apply appropriate friction based on risk signals while minimizing disruption to good users.
Build operational and platform tooling that helps risk and support teams efficiently manage case volume, exceptions, and high-touch cases.
Partner with data science to develop, deploy, and continuously improve machine learning models.
Establish and track metrics measuring risk effectiveness, operational impact, and customer experience impact.
Support the development of Mercury's risk capabilities so they can scale across its expanding product suite.