Staff Risk Analyst at EarnIn | Torre

Staff Risk Analyst

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Full-time

Legal agreement: Employment

Compensation
USD173k - 254k/year
location_on
Remote (for United States residents)
Shared by
Emma of Torre.ai
27 days ago

Responsibilities


About EarnInAs 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 SUMMARYWe are seeking a Staff Risk Analyst (Fraud) to partner closely with the Chief Risk Officer. This role is the single accountable owner of EarnIn's fraud risk management. You will operate as the company's fraud SME, setting direction, influencing architecture, and driving alignment across Engineering, Product, Compliance, and Fraud Ops.The scope goes well beyond analysis — you will own the full lifecycle from strategy through implementation and operations, and your impact will be felt across every product and every customer interaction at EarnIn.This is a remote position offering the opportunity to create meaningful impact in a dynamic, fast-paced fintech environment. The US base salary range for this full-time position is $173,928-$254,657, plus equity and benefits. Our salary ranges are determined by role, level, and location.WHAT YOU'LL DOFraud & Identity StrategyOwn the full fraud policy lifecycle — spanning identity verification, account opening, deposits, card transactions, and key monetary actions — from signal analysis and risk design through rule implementation, monitoring, iteration, and ongoing optimizationProactively identify emerging fraud vectors and redesign controls before losses materializeSupport AML rule design, simulation, and governance in partnership with Financial Crimes ComplianceCross-Functional Program LeadershipDefine the long-term fraud strategy that anchors roadmap priorities across Product and EngineeringLead fraud initiatives spanning Engineering, Product, Compliance, Fraud Ops, and external partners, including Visa and banking partnersServe as the primary escalation point during fraud incidents and ATO attacks — leading real-time response across teamsDrive alignment on risk decisions that balance fraud exposure, customer experience, and regulatory requirements simultaneouslyAnalytics & Organizational EnablementBuild and maintain fraud dashboards enabling real-time monitoring and self-serve analyticsMentor junior analysts and build knowledge transfer programs to scale fraud capability across the organizationWHAT WE'RE LOOKING FOR7+ years in analytics within fintech or consumer productsBachelor’s, Master’s, or PhD, or equivalent industry experienceDemonstrated experience with SQL and experience with Python or RExperience with external fraud platforms such as Visa Risk Manager, Socure, or equivalentExperience with Periscope, Tableau, Databricks, Amplitude, and/or Optimizely is a plusDemonstrated ability to lead cross-functional programs without formal authorityProven track record of driving structural improvements in fraud outcomes across multiple domains simultaneouslySkilled at using data to identify emerging fraud trends, quantify exposure, and translate analytical findings into actionable policy and control changesStrong understanding of how a credit card program works end-to-end — including transaction lifecycle, authorization and decline flows, dispute and chargeback processes, credit reporting obligations, and the relationship between card networks, issuing banks, and program managersStrong communicator who can translate fraud concepts for non-technical audiences and business requirements into system design decisionsComfortable operating under ambiguity and driving from incident to structured action quickly