7 дней назад
Fraud Lead (Consumer Lending)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Fraud Lead (Consumer Lending) (Fintech): Building fraud prevention strategy and decisioning architecture for a WhatsApp-based Send Now Pay Later lending product with an accent on repayment fraud, identity spoofing, chargebacks, and unit economics. Focus on designing dynamic rules, deploying machine-learning risk models, detecting synthetic identities and account takeover, and scaling automated blocking and investigation workflows.
Location: Currently fully remote, with a future transition to a hybrid setup centered around hubs in Miami, San Francisco, and New York
Company
is a hyper-growth Series C fintech building an AI-powered financial companion for Latinos in the US, combining conversational interfaces, real-time financial infrastructure, and crypto rails for remittances, credit, savings, and wallet services.
What you will do
- Define, architect, and refine first-party and third-party fraud typologies for the WhatsApp-based consumer lending ecosystem.
- Own repayment fraud, identity spoofing, chargeback, synthetic identity, and exploit-loop analytics for the Send Now Pay Later product.
- Manage fraud metrics including net fraud rate, false-positive ratios, challenge rates, and chargeback-to-sales ratios while protecting conversion.
- Design and orchestrate rules in decision engines such as Taktile, Provenir, and Alloy, and partner with Data Science on production machine-learning risk models.
- Design automated blocking protocols and manual investigation workflows with Operations and Engineering.
- Coordinate with Legal and Compliance on suspicious activity reports, loan abuse patterns, and regulatory requirements.
Requirements
- 4–5+ years of hands-on fraud risk strategy and prevention experience in consumer lending, BNPL, digital wallets, or credit cards.
- Advanced SQL skills, including BigQuery or Snowflake, plus Python, R, or business intelligence visualization tools for independent transactional analysis.
- Experience with modern decision engines such as Taktile, Provenir, Alloy, or similar platforms.
- Experience deploying, monitoring, and calibrating machine-learning risk models in live environments.
- Knowledge of emerging fraud attack vectors, account takeover, synthetic fraud, and OSINT-based threat detection.
- Strong communication skills for translating fraud patterns and technical metrics into business risks for executives, product managers, and engineering teams.
Culture & Benefits
- Currently fully remote, with a planned future hybrid, hub-centric work model.
- Initial stock options grant and annual performance bonus.
- 401(k), health, dental, and vision plans.
- Unlimited PTO and paid parental leave.
- Continuous learning and growth opportunities in an entrepreneurial environment.
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