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Senior Fraud Architect at Stripe (Remote, US)
Lead fraud-prevention strategy for Stripe users through Radar, combining threat investigation, risk-control optimization, and technical guidance. Turn fraud insights into measurable improvements across payments, accounts, and abuse prevention.
विवरण
- Own prevention strategies for assigned users, including risk baselines, threat models, and prevention plans
- Analyze Radar scoring, classifications, rules, and signal coverage using transaction evidence and technical context
- Explain fraud evidence and uncertainty while recommending configuration, integration, model, or feature changes
- Guide users in configuring and optimizing Radar, including the development and validation of rules, thresholds, and integrations
- Investigate payment, account, and behavioral abuse such as payment fraud, promotion abuse, multi-accounting, bots, and usage-based billing exploitation
- Lead weekly risk-health reviews and provide concise updates
- Set early-warning thresholds and notification paths, then convert fraud, dispute, approval-rate, and false-positive changes into prevention actions
- Track action plans with owners, deadlines, expected impact, and implementation status
- Coordinate incident communications, perform merchant-specific root-cause analysis, and confirm prevention effectiveness
- Work with Radar Product, Engineering, and Fraud Data Science to investigate limitations and define requirements
- Manage a cross-user backlog covering signal, model, integration, and payment-method gaps
- Create playbooks, investigation tools, and prevention frameworks while training Customer Success Managers, Technical Account Managers, and Account Executives
- Help shape account segmentation, coverage standards, tooling, hiring, incident handoffs, and program measurement
आवश्यकताएँ
- At least eight years in a technical role with substantial direct user engagement at a payments company, fintech, risk platform, or fraud-prevention provider
- Hands-on experience investigating fraud or abuse and converting findings into effective controls or user guidance
- Deep knowledge of payment fraud, account takeover, subscription or trial abuse, multi-accounting, dispute management, and network-monitoring programs such as VAMP, ECM, or EFM
- Technical understanding of API integrations, trace data, signal flows, system behavior, technical constraints, and implementation options
- Practical knowledge of machine-learning risk decisions and rule systems, including signal availability, model behavior, rules, and thresholds
- Proficiency in SQL plus Python, R, or a comparable language for hypothesis testing, pattern analysis, and control evaluation
- Ability to evaluate data quality, delayed fraud outcomes, precision, recall, false positives, and business impact
- Experience managing multiple user relationships or technical engagements and driving recommendations through implementation and measured outcomes
- Strong communication skills and sound product judgment
- Preferred: experience with Stripe Radar or comparable platforms such as Forter, Sift, Ravelin, or Signifyd
- Preferred: experience designing, testing, and tuning production fraud rules or thresholds
- Preferred: experience collaborating with product managers, engineers, and data scientists
- Preferred: familiarity with device intelligence, alternative payment methods, non-payment abuse prevention, or usage-based business models
- Preferred: experience building and scaling a technical advisory function or multi-account service model
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