Fraud Architect

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🏛️ Architect

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Stripe

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2010

💳 Fintech

🛍️ eCommerce

🤝 B2B

💰 Venture Round on 2021-05

Fintech • eCommerce • B2B

Stripe is a global payments processing platform that enables businesses to accept online and in-person payments. It offers a comprehensive suite of financial services, including payment processing, billing, and revenue management tools, aimed at businesses of all sizes, from startups to enterprises. By providing a developer-friendly API, Stripe allows businesses to streamline their payment operations and embed financial services directly into their applications, facilitating both B2B and B2C transactions.

📋 Description

• Own each assigned user’s prevention strategy, including risk baseline, threat model, and prevention plan • Investigate Radar scoring, classification, rule behavior, and signal coverage using transaction evidence and technical context • Explain fraud evidence and uncertainty and recommend configuration, integration, model, or feature actions • Help users configure and optimize Radar; develop and validate rules, thresholds, and integration recommendations • Investigate payment, account, and behavioral fraud patterns, including payment fraud, trial and promotion abuse, multi-accounting, bot activity, and usage-based billing exploitation • Run weekly risk-health reviews and share concise health updates • Establish early-warning thresholds and notification paths; translate fraud, dispute, approval-rate, and false-positive changes into prevention actions • Maintain action plans with owners, due dates, expected impact, and implementation status • Coordinate incident updates, conduct merchant-specific root-cause analysis, and verify prevention effectiveness • Partner with Radar Product, Engineering, and Fraud Data Science to investigate limitations and define requirements • Maintain a cross-user backlog of signal, model, integration, and payment-method gaps • Build playbooks, investigation tools, and prevention frameworks; train Customer Success Managers, Technical Account Managers, and Account Executives • Shape account segmentation, coverage expectations, tooling, hiring, incident handoffs, and program measurement

🎯 Requirements

• 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 effective controls or user guidance • Depth in 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 and signal flows, system behavior, technical limitations, and implementation options • Practical understanding of machine-learning-based risk decisions and rule systems, including signal availability, model behavior, rules, and thresholds • SQL proficiency and experience using Python, R, or a similar language for hypothesis testing, pattern investigation, and control evaluation • Ability to assess 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 results • Strong communication and product judgment • Preferred: experience with Stripe Radar or similar platforms such as Forter, Sift, Ravelin, or Signifyd • Preferred: experience designing, testing, and tuning fraud rules or thresholds in production • Preferred: experience partnering with product managers, engineers, and data scientists • Preferred: familiarity with device intelligence, alternative payment methods, abuse prevention beyond payments, or usage-based business models • Preferred: experience building and scaling a technical advisory function or multi-account service model