Data Scientist, All Levels
RampRemotePosted 11 February 2026
Job Description
About RampAt Ramp, we’re rethinking how modern finance teams function in the age of AI. We believe AI isn’t just the next big wave. It’s the new foundation for how business gets done. We’re investing in that future — and in the people bold enough to build it.Ramp is a financial operations platform designed to save companies time and money. Our all-in-one solution combines payments, corporate cards, vendor management, procurement, travel booking, and automated bookkeeping with built-in intelligence to maximize the impact of every dollar and hour spent. More than 50,000 businesses, from family-owned farms to e-commerce giants to space startups, have saved $10B and 27.5M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over $100 billion in purchases each year.Ramp’s investors include Lightspeed Venture Partners, Thrive Capital, Sands Capital, General Catalyst, Founders Fund, Khosla Ventures, Sequoia Capital, Greylock, Redpoint, and ICONIQ, as well as over 100 angel investors who were founders or executives of leading companies. The Ramp team comprises talented leaders from leading financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies such as Meta, Uber, Netflix, Twitter, Dropbox, and Instacart.Ramp has been named to Fast Company’s Most Innovative Companies list and LinkedIn’s Top U.S. Startups for more than 3 years, as well as the Forbes Cloud 100, CNBC Disruptor 50, and TIME Magazine’s 100 Most Influential Companies.About the RoleWe’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 DoFull stack development, building models to consume, transform, and expose data to stakeholders and production systemsDrive a culture of experimental design, testing agenda, and best practicesContribute 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 wayCollaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure successWork 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 actionWhat You NeedStrong knowledge of SQL (preferably Redshift, Snowflake, BigQuery) and how to write efficient SQL queriesFamiliarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboardsTrack record of shipping high quality products and features at scaleAbility to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutionsNice-to-HavesExperience 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 spaceFamiliarity with B2B enterprise sales cycle metrics and processesAbout Our TeamsProduct 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 i ... (truncated, view full listing at source)
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