Senior Data Analyst, Authentication Risk

<h2><span style="font-family: helvetica, arial, sans-serif;"><strong>About the Role</strong></span></h2> <p><span style="font-family: helvetica, arial, sans-serif;">We’re hiring a Data Analyst to join our Authentication Risk team, where you’ll play a critical role in preventing Account Takeover (ATO), reducing fraud losses, and protecting member trust. This role sits at the intersection of data, risk strategy, and product decisioning, with a strong emphasis on authentication flows, identity verification, and abuse prevention.</span></p> <p><span style="font-family: helvetica, arial, sans-serif;">You’ll partner closely with Product, Engineering, Analytics, DSML, and OMX to identify emerging attack patterns, design data-backed controls, and continuously improve authentication resilience while maintaining a seamless member experience.</span></p> <p><span style="font-family: helvetica, arial, sans-serif;">Your work will directly impact how we detect, prevent, and respond to authentication risk at scale helping ensure Chime remains both secure and easy to use for millions of members.</span></p> <p><span style="font-family: helvetica, arial, sans-serif;">The base salary offered for this role and level of experience will begin at $133,000.00 and up to $185,000.00. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.</span></p> <h2><span style="font-family: helvetica, arial, sans-serif;"><strong>In this role, you can expect to</strong></span></h2> <ul> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Analyze authentication and ATO-related risk signals to proactively identify fraud trends, abuse patterns, and control gaps, balancing loss reduction with member experience (40%)</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Partner with cross-functional teams to design, test, and deploy authentication and ATO prevention strategies, including product and policy changes across login, recovery, and verification flows (40%)</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Build and maintain dashboards and reporting to monitor authentication health, ATO rates, fraud losses, and member impact metrics (10%)</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Support ad-hoc risk investigations and analysis related to authentication abuse, incidents, andf emerging threats (10%)</span></li> </ul> <h2><span style="font-family: helvetica, arial, sans-serif;"><strong>To thrive in this role, you have</strong></span></h2> <ul> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">5+ years of experience in Fraud, Risk, Compliance, or Investigations, with exposure to ATO or authentication-related risk</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">2+ years of hands-on analytics experience, ideally in FinTech or a high-scale consumer platform</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Strong SQL skills and the ability to work comfortably with large, complex datasets</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Solid understanding of authentication mechanisms, account security risks, and industry fraud trends</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">Experience developing or influencing risk strategies, policies, or controls</span></li> <li style="font-family: helvetica, arial, sans-serif;"><span style="font-family: helvetica, arial, sans-serif;">High attention to detail with a strong bias toward structured, data-driven problem solving</span></li> <li style="font-family: helvetica, arial, sans-serif;"&gt