Data Scientist

About RampRamp 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 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 NeedMinimum of 4 years of industry experience as a Data ScientistStrong 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 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 market relationships.Growth Data | Ramp's Growth Data team ships data products and insights that allow Ramp to acquire new business and expand existing business and partnerships at scale. Current areas of focus include: Web & Martech, Outbound Automation, Customer Data Platform, Self-Service Product, GTM Strategic Finance, and Business Systems.Benefits available to all full-time Ramp employees (Global)Flexible PTOCentralized home-office equipment orderingHealth and wellness stipendBudget for intra-office travelWeekly coffee stipendUnited States100% medical, dental & vision insurance coverage for you, with partial coverage for dependentsOne Medical annual membership401(k), including employer match on contributions made while employed by RampFertility HRA (up to $10,000 per year)Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% payPet insuranceIn-office perks: lunch, snacks, drinks, and moreRelocation support to NYC or SF (as needed)CanadaGroup medical, dental, and vision coverage through Sun LifeLife, AD&D, and disability coverageFertility drug coverage (up to $4,000 lifetime)Group Retirement Plan with employer match (RRSP + DPSP)Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced payEmployee Assistance Program and virtual care through Lumino HealthUnited KingdomPrivate medical insurance through Freedom EliteVirtual GP and at-home care via eMed x LiviWorkplace pension through Penfold, with salary sacrifice optionParental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced payReferral InstructionsIf you are being referred for the role, please contact that person to apply on your behalf.Other noticesPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.Ramp Applicant Privacy NoticeCompensation Range: $137,120 - $297,330LocationNew York, NY (HQ); Remote (US); San Francisco, CAEmployment TypeFull timeLocation TypeHybridDepartmentDataCompensationSF/NYTarget Base Salary $137,120 – $297,330 • Offers EquityNationwideTarget Base Salary $137,120 – $297,330 • Offers EquityThe final compensation will depend on the location and level at which the candidate is hired.