Fraud Lead - Consumer Lending

Felix Technologies•Washington, WA

5d•Remote

About The Position

Félix is hiring a Fraud Lead for Consumer Lending to protect the unit economics of its Send Now Pay Later (SNPL) product. This high-visibility, cross-functional role reports directly to the Head of Credit Risk and has a dotted line into the broader Fraud Organization. The Fraud Lead will define, build, and refine fraud prevention frameworks for WhatsApp-based conversational lending and digital cross-border lending, identifying attack vectors and deploying dynamic decisioning logic while supporting secure, profitable growth. The role covers fraud strategy, repayment and payment analytics, ownership of fraud performance metrics, decision-engine architecture, operational policy design, and coordination with Legal and Compliance. The Fraud Lead will work with Operations, Engineering, and Data Science to implement fraud controls and monitor risk models, while balancing fraud prevention with customer conversion.

Requirements

4–5+ years of hands-on experience in Fraud Risk Strategy and Prevention, specifically in consumer lending, BNPL, digital wallets, or credit card ecosystems.
Advanced SQL skills, including tools such as BigQuery or Snowflake, and experience with Python/R or BI visualization tools to independently extract, analyze, and model transactional logs.
Experience with modern decision engines such as Taktile, Provenir, Alloy, or similar, and deploying or monitoring machine-learning risk models in live environments.
Deep understanding of emerging fraud attack vectors, account takeover (ATO), and synthetic fraud, with experience using data and OSINT techniques for threat detection.
Ability to communicate complex fraud patterns and technical metrics as actionable business risks to executives, product managers, and engineering teams.
Builder mentality and experimental approach, with the ability to turn data insights into policy execution with speed, precision, and independence.
Equivalent competencies in the listed areas will also be considered.

Responsibilities

Design, launch, and continuously refine first-party and third-party fraud typologies for the WhatsApp conversational lending ecosystem.
Own repayment fraud, identity spoofing, and chargeback analytics for SNPL payments; identify exploit loops and synthetic identities, and implement preemptive transaction blocks.
Drive accountability for core fraud metrics, including net fraud rate, false positive ratios, challenge rates, and chargeback-to-sales ratios, across the lending vertical while protecting conversion.
Own rule design and logic orchestration in modern decision engines, and partner with Data Science to deploy, monitor, and calibrate machine-learning risk models in production.
Partner with Operations and Engineering to design, optimize, and scale automated blocking protocols and manual investigation workflows.
Coordinate with Legal and Compliance to monitor, flag, and report Suspicious Activity Reports (SARs), loan abuse patterns, and system exploitation in alignment with regulatory standards.