Jobs / United States / Ramp Business Corporation
Data Scientist
Ramp Business Corporation · 🇺🇸 New York, NY (HQ); San Francisco, CA; Remote (US) · 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 53 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 2 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 Ramp Business Corporation paid sponsored hires in similar roles2 certified filings for “DATA SCIENTIST L3 TIER 1” (Data Scientists) in NY: $112k–$280k, median $196k. 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.
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Sponsor Radar — Ramp Business Corporation
The US Department of Labor certified 53 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 2 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 Ramp Business Corporation →
About the role
ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE We’re looking for someone to help lead the future of analytics at Ramp. This person will enable Ramp to get 1% better every day by developing data products and insights. They will partner closely with business stakeholders and product, engineering, and design counterparts to prioritize and execute on work, improve reporting, as well as drive results and process improvements. WHAT YOU’LL DO - Full stack development, building models to consume, transform, and expose data to stakeholders and production systems - Drive a culture of experimental design, testing agenda, and best practices - Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will allow us to make better decisions in a scalable way - Collaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure success - Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights, and partner with business teams to turn those insights into action WHAT YOU NEED - Minimum of 4 years of industry experience as a Data Scientist - Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery) and how to write efficient SQL queries - Familiarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboards - Track record of shipping high quality products and features at scale - Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions NICE-TO-HAVES - Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hightouch or equivalents) - Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development) - Experience within the payments and financial technology space - Familiarity with B2B enterprise sales cycle metrics and processes ABOUT OUR TEAMS - Product Data | Ramp’s Product Data team is responsible for delivering data products and insights that shape Ramp’s product direction and unlock business value. The Product Analytics team is also responsible for building out the platform through which new products are launched, instrumented, tested, and QA’d. The team embeds deeply as a partner to engineering, product, and design. - Risk & Capital Markets Data | Ramp’s Risk Data team is responsible for how risk is evaluated, and building the risk infrastructure to scale to millions of businesses in the United States. Areas include risk operations and underwriting, limit setting and pricing across financial products as well as fraud detection, regulatory reporting, and capital ma