Jobs / United States / Stripe
Data Analyst, Intern
Stripe · 🇺🇸 New York, Seattle, South San Francisco HQ
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 roles2 certified filings for “Data Analyst” (Data Scientists) in NY: $109k–$170k, median $140k. Most were filed at wage level II (50%) — 2 lottery entries, ≈31% 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.
Or apply yourself on the official page →
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 technology company focused on improving the conditions for economic growth and prosperity. We build programmable financial infrastructure, rethinking from first principles how financial services should work, to make it easier and cheaper for any business to start and scale. More than 10 million businesses build on Stripe, spanning the economic frontier—from solo founders to established enterprises—united by a practical focus on growth. The most ambitious companies in the world use Stripe as core infrastructure to grow faster. They process trillions of dollars a year on Stripe, equivalent to around 1.6% of global GDP. While economic growth makes everyone better off, open markets also enable greater variety. When any business can easily serve a global customer base, the quality and diversity of products in the world increase, and craft and creativity are unleashed into the smallest niches. Our own growth is wholly contingent on the success of the businesses building on Stripe. We therefore invest back into our technology at an unusual rate. We make upgrades to our products every single day to deliver compounding gains to our customers. We maintain some of the most reliable APIs on the internet. We build entirely new pieces of financial infrastructure to enable new ideas. And our significant advances in risk and fraud infrastructure over many years are making the internet economy safer and more accessible. Though people at Stripe don’t tend to take themselves seriously, Stripe is a fairly serious place: our customers are depending on us for their livelihoods. We admire ambition, intensity, curiosity, humility, and rigor. The most effective people become knowledgeable about many domains besides their own. Any company is an applied exercise in understanding some aspect of society or the market. In working with so many (especially the new and innovative ones), we think that Stripe is one of the very best places to learn about how the world works. About the team Data Science at Stripe is a vibrant community where data analysts and data scientists learn and grow together. You'll work with some of the most fundamental data at Stripe, and use that data to help drive company-wide initiatives. We have a variety of Data Analytics roles and teams across Stripe and will seek to align you to the most relevant team based on your background. What you’ll do As an intern at Stripe you’ll work on projects across our stack that directly impact the way millions of businesses operate. You’ll own problems end to end with the support of your manager and teammates. It’s an opportunity to work alongside some of the most creative and technically rigorous data analysts and scientists in the industry. You'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. You'll work closely with partners to extract insights from the rich and complex data at Stripe. You'll build metrics, scalable data pipelines, dashboards, and reports to inform and run the business. You'll deliver actionable business recommendations through analyses and data storytelling. Our internship program is competitive and the expectations are high. Responsibilities • Analyze data and running experiments to drive impact • Ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly • Create metrics, reports, and dashboards to inform and run the business • Extend Stripe’s metrics semantic layer • Build new data assets and improve existing data assets to support decision-making, products, and business processes • Assess the impact of