As one of the first pioneers of earned wage access, our passion at EarnIn is building products that deliver real-time financial flexibility for those with the unique needs of living paycheck to paycheck. Our community members access their earnings as they earn them, with options to spend, save, and grow their money without mandatory fees, interest rates, or credit checks.
We’re fortunate to have an incredibly experienced leadership team, combined with world-class funding partners like A16Z, Matrix Partners, DST, Ribbit Capital, and a very healthy core business with a tremendous runway. We’re growing fast and are excited to continue bringing world-class talent onboard to help shape the next chapter of our growth journey.
POSITION SUMMARY
EarnIn's Risk Analytics team is looking for a detail-oriented and technically driven Data Analyst to join our Fraud Analytics function. This is a role focused on fraud detection, monitoring, and operational support. You will work closely with the Fraud Operations team and senior fraud analytics staff to ensure continuous, high-quality fraud monitoring that protects our customers and the business. This role is based in Bengaluru and plays a critical part in our fraud monitoring coverage, providing timely analytical support across time zones. This position will be a hybrid role based in our Bengaluru office, as part of our expanding site presence, with 2 days per week in the office. EarnIn offers excellent benefits for our employees, including healthcare, internet and cell phone reimbursement, a learning and development stipend, and potential opportunities to travel to our headquarters in Mountain View. Our salary ranges are determined by role, level, and location.
WHAT YOU'LL DO
Fraud Monitoring & Reporting
• Own and deliver recurring fraud reporting on a reliable cadence, ensuring key stakeholders receive timely and accurate insights into fraud patterns and anomalies.
• Monitor fraud metrics and signals continuously, flagging emerging threats and anomalous patterns for rapid response.
• Maintain and improve existing dashboards and reporting pipelines to reflect evolving fraud typologies.
Fraud Investigation Support
• Collaborate with the Fraud Operations team on fraud and dispute case investigations, providing data-driven analysis to improve case turnaround time and decision quality.
• Conduct deep-dive analyses on specific fraud events or trends to support operational triage and escalations.
• Document findings and contribute to internal knowledge bases for fraud patterns and investigative playbooks.
Ad-Hoc & Strategic Analysis
• Execute ad-hoc analytical projects, including external vendor data studies, to inform fraud tooling and partnership decisions.
• Support the evaluation of new fraud detection vendors and data providers through structured comparative analyses.
• Contribute to strategic fraud initiatives by providing quantitative insights and analytical frameworks.
Automation & Tooling
• Leverage AI-powered tools and automation to improve efficiency in repetitive analytical workflows.
• Identify opportunities to streamline data pipelines, reporting processes, and investigative workflows.
WHAT WE'RE LOOKING FOR
• Bachelor's degree in Engineering, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Proficiency in Python (Pandas, NumPy) and SQL for data extraction, transformation, and analysis.
• Experience building or maintaining data pipelines, dashboards, or analytical reports.
• Strong analytical thinking with an ability to identify patterns in complex, high-volume datasets.
• Excellent communication skills — able to present findings clearly to both technical and non-technical stakeholders.
• Demonstrated coach-ability, intellectual curiosity, and a proactive approach to learning and feedback.
At EarnIn, we believe that the best way to build a financial system that works for everyday people is by hiring a team that represents our diverse community. Our team is diverse not only in background and experience but also in perspective. We celebrate our diversity and strive to create a culture of belonging. EarnIn does not unlawfully discriminate based on race, color, religion, sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), gender identity, gender expression, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, registered domestic partner status, sexual orientation, genetic information, or any other basis protected by local, state, or federal laws. EarnIn is an E-Verify participant.
EarnIn does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or HR team.
What We Do
Earnin’s mission is to build a financial system that works for people. Every year, while Americans wait for their paychecks, more than $1 trillion of their hard-earned money is held up in the pay cycle. As a result, we accumulate over $50 billion in late and overdraft fees and turn to high-interest loans. We seek to eliminate those fees and put money back into workers’ hands. Our financial system doesn’t work for people. But Earnin does. Earnin is an app that lets people get paid as soon as they leave work, with no fees, interest, or hidden costs. App users can receive their money in their bank account instantly at little or no cost — as we operate on a pay what you choose model. All they need is a bank account and a job that provides direct deposit or uses electronic timesheets. At Earnin, we’re building the way we think a financial system should work for everyone, not just the people who can afford it. We help people take control of their money and get to a better financial place. Our goal is not only to provide great products at little or no cost to the people who need them but also to inspire kindness across the financial world and eventually across all industries.









