Fraud Lead - Consumer Lending

Felix is hiring a Fraud Lead - Consumer Lending in Buenos Aires, Argentina. Level rates it ; you can apply on Felix.

Level's read on this job

Little AI ●○○○ is how Level rates this role: aI is not part of the work.
Tools and skills the posting cites include Whatsapp, MLOps and fraud detection.
Level classifies it as a lead role.
Level lists 116 other open roles at Felix.
The role was posted within the past week.

AI in this role

Protect unit economics for Send Now Pay Later products by building fraud prevention frameworks at the intersection of chat interfaces and lending.

ml-opsfraud-detectionrisk-managementdata-analysisconsumer-lending

About Us

At Félix, we are building the indispensable financial companion for Latinos in the US. We combine an AI-powered, conversational-first interface with real-time financial infrastructure to make cross-border money movement as easy as sending a text. Starting with fast, affordable remittances powered by AI and crypto rails, we are expanding into credit, savings, and wallet services to support the complete immigrant financial journey. Our ambition is to deliver a white-glove financial experience with the simplicity of a conversation to a community the traditional financial system has historically overlooked.
We are a hyper-growth Series C company, backed by over $300 million in funding from top-tier global investors, including Andreessen Horowitz, QED, Castle Island, Switch Ventures, HTwenty, Monashees, General Catalyst Customer Value Fund. This isn't just about the numbers; it's a testament to the trust our investors have in our vision and our team. Additionally, Félix was selected as an “Endeavour Entrepreneur” and was a recipient of the CrossTech Fintech Startups Award.
Joining Félix means you will be part of a team building a legacy, a company that will outlive us all. This is a rare opportunity to apply your skills to a deeply meaningful mission—serving a community that has been underserved for too long because we are obsessed with our customers. We get things done with urgency and focus, driven by extreme ownership over our impact. We collaborate without ego, fostering radical transparency and fierce loyalty so we can grow together. Because we aim for insanely great rather than just good enough, we stay insatiably curious—always experimenting, building the future today, and delivering a product that truly makes our users' lives better.
About the Role
As our Fraud Lead for Consumer Lending, you will be the core architect and gatekeeper protecting the unit economics of our Send Now Pay Later (SNPL) product. This is a high-visibility, cross-functional role reporting directly to the Head of Credit Risk, with a dotted line into our broader Fraud Organization.You will be responsible for defining, architecting, and mitigating fraudulent behaviors at the intersection of instant conversational interfaces (WhatsApp) and digital cross-border lending. We need an autonomous, highly analytical fraud specialist who can build prevention frameworks from scratch, identify sophisticated attack vectors, deploy dynamic decisioning logic, and ensure that our business growth remains secure and highly profitable.
Responsibilities

Fraud Strategy & Architecture: Design, launch, and continuously refine first-party and third-party fraud typologies specifically tailored to our WhatsApp conversational lending ecosystem.
Payment & Repayment Analytics: Own repayment fraud, identity spoofing, and chargeback analytics for SNPL payments, proactively identifying exploit loops, synthetic identities, and implementing preemptive transaction blocks.
Unit Economics & Metric Ownership: Drive and hold direct accountability for core fraud metrics (e.g., net fraud rate, false positive ratios, challenge rates, chargeback-to-sales ratios) across the entire lending vertical without hindering conversion.
Decision Engine Architecture: Own rule design and logic orchestration within modern decision engines (e.g., Taktile, Provenir, Alloy) and partner with Data Science to deploy, monitor, and calibrate Machine Learning risk models in production.
Operational Policy Design: Partner closely with Operations and Engineering teams to design, optimize, and scale automated blocking protocols alongside efficient manual investigation workflows.
Regulatory & Compliance Liaison: Coordinate with Legal & Compliance to monitor, flag, and report Suspicious Activity Reports (SARs), loan abuse patterns, and system exploitation in alignment with regulatory standards.

Requirements

Fintech & Lending Core: 4–5+ years of hands-on experience in Fraud Risk Strategy and Prevention, explicitly within consumer lending, Buy Now Pay Later (BNPL), digital wallets, or credit card ecosystems.
Data Analytics Mastery: Advanced skills in SQL (BigQuery, Snowflake, etc.) and data manipulation (Python/R or BI visualization tools) to extract, analyze, and model transactional logs independently with total autonomy.
Rule Engine & MLOps Exposure: Proven experience working with modern decision engines (such as Taktile, Provenir, Alloy, or similar) and deploying/monitoring machine learning risk models in live environments.
Investigative & OSINT Mindset: Deep understanding of emerging fraud attack vectors, account takeover (ATO), and synthetic fraud, with a track record of using data and OSINT techniques for threat detection.
Exceptional Cross-Functional Communication: Strong ability to translate complex fraud patterns and technical metrics into actionable business risks for C-suite executives, product managers, and engineering teams.
Extreme Ownership: A true builder mentality with an experimental spirit, capable of moving from high-level data insights down to policy execution with speed, precision, and zero hand-holding.
These are the applicable requisites, although equivalent competencies in any of the above will also be considered.

What We Offer

Competitive salary
Initial stock options grant
Annual performance bonus
Work model: currently fully remote, with a future transition to a hybrid set up
Health, dental, and vision plans
Continuous learning opportunities
Unlimited PTO
Paid parental leave
Empowering opportunities for growth in a dynamic entrepreneurial environment

Equal Opportunity Employer
At Félix, we are committed to providing equal employment opportunities to all qualified employees and applicants without regard to race, religion, nationality, sex, sexual orientation, gender identity, age, or disability. This policy applies to all terms and conditions of employment, including recruitment, hiring, placement, promotion, training, compensation, benefits, and termination.
Want to learn more about our privacy practices? Check out our Privacy Policy.

How we rate this

Fraud Lead - Consumer Lending at Felix rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Fraud Lead - Consumer Lending is an open job at Felix.
Level rates this role AI Level 1 of 4: Little AI.
The role is based in Buenos Aires, Argentina.
The job was posted on November 2, 2026.
Seniority: lead.
Applications are handled by Felix. Apply on Felix

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsFraud DetectionRisk ManagementData AnalysisConsumer LendingWhatsapp

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a project where fraud detection was part of your work. What did you do?
Tell me about a project where risk management was part of your work. What did you do?
Tell me about a project where data analysis was part of your work. What did you do?
Tell me about a project where consumer lending was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: ML Ops, Fraud Detection, Risk Management, Data Analysis, and Consumer Lending. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

Get your CV reviewed before you apply

Send your CV and the role you want next. Your review arrives by email within 3 days.

Get a free CV review Check your resume with the ATS resume checker