Member of Technical Staff

About the role

This role is responsible for defining and executing the fraud strategy for one of the fastest-growing consumer fintech companies in Latin America. You will own the full lifecycle of fraud detection, mitigation, and operations across digital channels, directly shaping product and policy with the founders. Within your first three weeks, you will conduct an independent assessment of the entire fraud surface and own the roadmap from findings to execution. You will build a precision-first detection system that protects over $500MM in annualized GMV while minimizing friction for legitimate users. The role requires deep ownership of both strategic planning and hands-on implementation, including running experiments and iterating on controls in production. You will establish the fraud operations function and create feedback loops that turn manual case reviews into automated intelligence. Success in this position means the company can confidently scale user acquisition and transaction volume without being undermined by programmatic attacks.

Key facts

What you'll do

Perform an independent fraud risk assessment of Nelo's entire ecosystem within three weeks of start date, identifying critical weaknesses and prioritizing remediation.

Design and launch a step-up authentication experiment within five weeks aimed at improving challenge rates and precision to best-in-class levels.

Lead initiatives to reduce first-payment default by at least 3 percentage points for a target segment within one month while minimizing impact on approval rates.

Build a repeatable fraud operations system within three months that generates intelligence from manual case reviews, leveraging AI agents, human agents, or both.

Implement controls to cap all currently uncapped fraud risk vectors, ensuring that programmatic acquisition, transaction, and account takeover risks are reduced to negligible levels within six months.

Own the precision-first design of detection systems, balancing recall requirements with strict operational discipline around user experience.

Collaborate directly with product, engineering, and compliance teams to embed fraud controls into new features from conception through production deployment.

Analyze large-scale behavioral and transactional data to detect emerging fraud patterns and validate the effectiveness of mitigation measures.

Define key metrics and dashboards for fraud performance, maintaining transparency with leadership through clear reporting and actionable insights.

Continuously challenge existing rules and models, iterating rapidly to ensure the fraud stack remains adaptive to evolving adversarial tactics.

Requirements

You have owned a fraud domain end to end, reviewing cases in your area, deploying high-precision rules or models into production, and iterating based on performance.

You run AI agents in a meaningful capacity today and are building toward self-improving feedback loops for agentic systems.

Your analysis stands on its own, with nobody double-checking your work for technical correctness, and you understand every line of SQL your agents write.

You step through every screen a user will see before a control ships, and you can intuit what good and bad product experiences look like for both good users and fraudsters.

You can take charge during an incident, tell people exactly what to do to close the gap on an active threat, and persuade the room with evidence even when the fix is unpopular.

People like working with you, which makes your persuasion effective when trade-offs between risk, speed, and user experience are being debated.

You are legitimately paranoid about unmitigated risk in a fintech environment with a lending business moving more than $500MM in annualized GMV.

You are comfortable making decisions with incomplete information and documenting your reasoning so that it can be audited and improved over time.

Nice to have

Experience in financial services fraud, particularly in acquisition, transaction, or account takeover risk.

Background building and operating detection systems at scale, including log-in challenge flows and precision-oriented rule engines.

Familiarity with product-led growth environments where experimentation velocity and user experience are tightly coupled.

Experience working with AI agents in production and designing feedback mechanisms for continuous improvement.

Practical notes

This role is based in New York City and is a full-time position. No additional information regarding hours, travel, visa, or deadlines was provided in the source material.