Fraud Architect

What you'll do

• Maintain account risk baselines, threat models, and prevention plans; conduct regular risk reviews and follow actions through implementation and verification.
• Investigate fraud patterns, Radar behavior, integrations, and signals; recommend and validate rules, thresholds, and other protections.
• Coordinate incident analysis and product feedback with users and internal teams, and build reusable playbooks and prevention frameworks.

What they ask for

• 8+ years in a technical role with substantial direct user engagement at a payments company, fintech, risk management platform, or fraud-prevention provider.
• Hands-on experience investigating fraud or abuse and translating findings into controls or user guidance; depth in payment fraud and related abuse or dispute topics.
• Technical understanding of API integrations, data and signal flows, machine-learning-based risk decisions, and rule systems.
• SQL proficiency and experience using Python, R, or a similar language for investigations and control evaluation; experience managing user relationships and driving recommendations through implementation.

Nice to have

• Experience with Stripe Radar or similar platforms such as Forter, Sift, Ravelin, or Signifyd.
• Experience tuning fraud rules in production or partnering on model and signal improvements; familiarity with device intelligence, alternative payment methods, or usage-based business models.

Tools

Radar, SQL, Python, R, Forter, Sift, Ravelin, Signifyd

AI focus

Applies practical understanding of machine-learning-based risk decisions and collaborates with product, engineering, and fraud data science teams on model or signal gaps; no AI development is stated.