Jobs / United States / Ripple Labs INC

Staff Data Scientist

Ripple Labs INC · 🇺🇸 San Francisco, CA, United States

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 26 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 17 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 Ripple Labs INC paid sponsored hires in similar roles1 certified filing for “Data Scientist” (Data Scientists) in NY: $183k–$183k, median $183k. Most were filed at wage level II (100%) — 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.

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Sponsor Radar — Ripple Labs INC

26 H-1B filings certified since Oct 2025

The US Department of Labor certified 26 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 17 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 Ripple Labs INC →

About the role

At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs. If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value. At Ripple, we’re building a world where value moves like information does today. It’s big, it’s bold, and we’re already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs. If you’re ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value. THE WORK We're looking for a Staff Data Scientist to be the technical lead across Ripple's diverse product and business portfolio. You'll define the analytics vision, build the scientific frameworks the org uses to evaluate product and business performance, and use AI tooling to accelerate the speed and reach of analytics across the company. In this role, you'll partner with product and business leads to frame the most important questions, set the analytical bar, and ensure decisions across surfaces rest on a consistent, thorough foundation. You'll operate as a force multiplier -- solving the hardest problems, building the frameworks others reuse, and leveling up data scientists across teams. WHAT YOU'LL DO • Be the DS tech lead across multiple product and business teams: setting methodological standards and unblocking the hardest analytical problems across areas including Payments, Stablecoin & Custody products. • Partner with product and business leads to define analytics strategy : shaping which initiatives to invest in, what success looks like, and how we'll know. • Build the scientific frameworks Ripple reuses at scale : product and network health metrics, causal inference playbooks, liquidity and adoption models, and forecasting approaches that work across institutional and developer surfaces. • Pioneer AI-accelerated analytics : applying LLMs and agentic workflows to scale insight generation, automate routine analysis, and enable self-serve exploration for non-DS partners. • Drive evidence-based evaluation of growth across customers, corridors, and on-chain activity, surfacing the causal drivers behind adoption and volume. • Define and communicate the metrics leadership runs on : translating complex results into clear narratives for Ripple executives and external stakeholders. • Raise the bar for the DS function through thought leadership and mentorship across embedded teams. WHAT YOU'LL BRING • 8+ years in data science or quantitative analysis, with a track record of senior level impact across multiple teams. • Demonstrated technical leadership across cross-functional teams , influencing roadmaps and strategy at both executive and execution levels. • Proven experience designing reusable analytics and measurement frameworks that scale across products. • Hands-on experience applying AI to accelerate analytics workflows (agentic analysis, AI-assisted insight generation, natural-language data interfaces). • Deep expertise in experimentation, causal inference, forecasting, and statistical modeling in a product e

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Source: Greenhouse (employer board) First seen: 2026-10-15 Last confirmed: 2026-10-15 How our data works → Report this job

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