Fraud Lead - Consumer Lending

Félix

Buenos Aires

Remote

ARS 185,448,000 - 293,627,000

Full time

3 days ago
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Benefits offered by this job

Initial stock options grant
Annual performance bonus
Unlimited PTO
Paid parental leave
Remote work

Job summary

Félix is seeking a Fraud Lead for Consumer Lending to defend the SNPL product across a fully remote organization. This role reports to the Head of Credit Risk and collaborates with the Fraud Org.

You will architect fraud prevention, identify advanced attack vectors, deploy dynamic decisioning, and ensure secure, profitable growth in cross-border lending. You will partner with Data Science to monitor models, design blocking protocols, and align with regulatory standards while enabling scalable,

Qualifications

  • 4–5+ years in Fraud Risk Strategy and Prevention in consumer lending, BNPL, digital wallets, or credit card ecosystems.
  • Advanced SQL and data manipulation (Python/R or BI tools) to analyze transactional logs independently.
  • Experience with modern decision engines (Taktile, Provenir, Alloy) and deploying ML risk models in production.
  • OSINT mindset with knowledge of fraud vectors, account takeover, and synthetic fraud.
  • Strong ability to translate fraud patterns and metrics for executives, product, and engineering.

Responsibilities

  • Fraud strategy: design, launch, and refine first-party/third-party fraud typologies for our WhatsApp lending ecosystem.
  • Analytics: own repayment fraud, identity spoofing, and chargeback analytics to detect exploits.
  • Unit economics: own fraud metrics across lending verticals without hurting conversions.
  • Decision engine: design rules and orchestrate logic with data science to deploy risk models.
  • Operational policy: work with Ops and Eng to scale automated blocking and efficient investigations.
  • Regulatory liaison: coordinate with Legal to monitor SARs and compliance.

Skills

Fraud risk strategy
Data analytics
Cross-functional communication
Ownership mindset
OSINT mindset

Tools

Taktile
Provenir
Alloy
BigQuery
Snowflake

Job description

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.

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