Member of Technical Staff - Head of Fraud

About this role

MEMBER OF TECHNICAL STAFF - HEAD OF FRAUD

About the Company

Nelo is a leading fintech in Mexico reimagining credit to expand consumer buying power. Founded in 2019 by former Uber international growth team leads Kyle Miller and Stephen Hebson, Nelo offers credit cards, BNPL loans, bill payments, and its own marketplace — all under one app — designed from first principles for a mobile-first, real-time payments world.

With $100M in annual revenue, $1B in annualized GMV, and $140M+ raised in equity and debt, Nelo is one of the most capital-efficient consumer fintech companies in Latin America. The company is profitable — positive operating profit in both 2024 and 2025. It runs lean and technical: 60 employees, 8 engineers, with AI driving underwriting, collections, and operations.

- HQ: Mexico City, Mexico; commercial and people operations in New York City

- Founded: 2019

- Team size: 60 FTEs

- Open roles: 10+

- Website: nelo.mx http://nelo.mx

- Stage: Post-Series A; $100M credit facility (Victory Park Capital, 2022); profitable

- Benefits: 401k, open PTO, medical, dental, vision, STD, LTD, fertility

Company values:

- Be your best selves: ambition, hard work, intellectual curiosity

- Everyone is an owner: all employees receive equity including customer support; 10-year option expiration; equity refreshers

- Customer first: product decisions grounded in customer benefit

- Open and honest communication: quarterly financials and board presentations shared company-wide; low tolerance for bureaucracy or gossip

- Move fast, learn fast: hundreds of experiments run monthly; rigorous experimentation culture

WHY THIS ROLE IS DIFFERENT

In most companies, fraud is a cost center. You inherit a rules engine someone else built, you tune thresholds inside guardrails someone else set, and success means losses stayed flat.

The mandate here is bigger. In your first three weeks you will run an independent assessment of Nelo's entire fraud surface and write the roadmap yourself. You will own detection, mitigation, and the operating function behind them, end to end, on a lending business moving more than $500MM in annualized GMV.

The mandate is precision first: we would rather challenge almost nobody and be right than blanket good users with friction. You will build the fraud ops function as an agent-operated system from the start, and you will work directly with the founders. Whether a programmatic attack against Nelo is even possible six months from now depends on the controls you put in place.

WHAT YOU'LL DO

Role mission: Engineer a fraud detection and mitigation system that maximizes precision first, then recall.

1. Fraud threat assessment. Within three weeks of start date, produce an independent fraud risk assessment of Nelo. Where are our biggest weaknesses? What is on fire, or a greater risk than we previously believed? What roadmap follows from those findings?

2. Step-up optimization. Best-in-class log-in challenge rates are ultra-high precision and very low in relative terms. Within five weeks of start date, launch a test intended to get us to our challenge rate and precision goals.

3. Acquisition fraud (if your background is in financial services). Much of our fraud in dollar terms is first-party fraud at time of acquisition: a tough problem, and one rich in opportunity. Within one month of start date, launch an experiment that reduces first payment default rate by 3 percentage points for a segment, with the smallest possible impact to approval rate.

4. Establish the fraud ops function. Within three months of start date, build a system that generates repeatable intelligence from a manual fraud case review feedback loop, whether with AI agents, human agents, or both.

5. Cap any currently uncapped fraud risk. Within six months of start date, the risk of an unmitigated, programmatic fraud attack (acquisition, transaction, ATO) should be reduced to negligible because of controls you have put in place. This is the number one outcome for this role.

WHY YOU SHOULD APPLY

- You have owned a fraud area before: reviewing cases in your domain, deploying high-precision rules or models to production, and iterating until the fraudsters give up and go bother someone else.

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

- Your analysis stands on its own. Nobody double-checks 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. You can intuit what good and bad product experiences look like, for good users and for 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 when the fix is unpopular. People like working with you, which makes the persuasion stick.

- You are legitimately paranoid about new threat vectors, and it shows in your work.

WHY YOU SHOULD NOT APPLY

- You want a mature fraud stack with an established playbook. Most of this does not exist yet. You are building the function, not stepping into one.

- Your background is purely fraud data science or purely fraud ops. This role sits in fraud strategy and analytics with production ownership, and it needs both the judgment and the shipping.

- You have not started working with AI agents, or you think they are a gimmick. The fraud ops function you build will be agent-operated from day one, and every team at Nelo uses AI daily.

- You prefer setting rules from a distance and letting the consequences follow. We walk every user-facing flow before shipping a control.

- You want a machine that is already fully optimized. We are discovering the correct credit box as we go, and that takes a lot of work. If that is unpalatable to you, that is fine, but this role is not for you.

- You cannot commit to 80%

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