Jobs / United States / Stripe
Fraud Patterns Analyst
Stripe · 🇺🇸 US-Remote · Remote
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 260 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 64 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Stripe paid sponsored hires in similar roles5 certified filings for “Data Analyst” (Data Scientists) in CA: $195k–$212k, median $195k. Most were filed at wage level IV (60%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Stripe
The US Department of Labor certified 260 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 64 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Stripe →
About the role
Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world's largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team The Risk Operations team is looking for an experienced fraud analyst to join an industry-leading global fraud operations team. This position is responsible for writing and maintaining fraud rulesets to prevent transaction fraud, conducting data analysis to identify and mitigate fraud attacks, while minimizing impact to users, and working collaboratively with fraud, operations, and product stakeholders to proactively implement fraud strategies and controls. They should have a deep understanding of fraud patterns and typologies, advanced SQL proficiency, strong analytical abilities, and experience writing and managing fraud rulesets. What you'll do Did you know that only around 4% of the world's GDP comes from internet commerce? At Stripe, we believe that this represents a future with almost limitless potential for innovation, creativity, and global prosperity. While the promise of a global online economy is palpable, it doesn't come without significant risk. Each day, bad actors disrupt the trust and safety of the internet and increase the barrier of entry for online businesses. Before we can fully realize the potential of a global internet economy, we must first address the burgeoning problem of fraud. We are looking for someone passionate about fighting fraud, identifying new trends and typologies, conducting complex data analysis, and working collaboratively with peers and partners in the fraud space. This position works closely with cross-functional stakeholders across product, engineering, data science, and operations to identify and mitigate risk from complex, distributed transaction fraud attacks. The right candidate for this role will have a minimum of five years' experience conducting advanced data analysis using SQL, preferably within the fraud space across e-commerce, payments, or cryptocurrency. Candidates should have experience writing, maintaining, and analyzing complex fraud rulesets and demonstrated success minimizing fraud losses along with impacts to users. Candidates should also have experience working closely with product teams to implement risk controls and demonstrate a deep understanding of fraud typologies, controls, and ability to mitigate fraud risk. Responsibilities • Build and maintain fraud rulesets to prevent transaction-level fraud losses, including ongoing monitoring and measurements of precision and recall • Conduct advanced data analysis of structured and unstructured data sets to proactively identify emerging fraud attacks impacting Stripe and its users • Collaborate closely with product, risk, and operations teams to proactively identify and mitigate fraud exposure • Investigate, conduct root cause analysis, and deploy remediations to prevent future complex and distributed fraud attacks • Investigate and take action against anomalous clusters of transactions based on account activity, processing volume, or other risk indicators while minimizing negative impacts to Stripe users • Respond to incidents involving complex fraud schemes to quickly mitigate exposure to Stripe, its users, and financial partners • Utilize analytics to identify and implement initiatives to automate manual processes and workload across the organization • Create visualizations, d