{"id":14049,"url":"https://alion.io/job/ramp-data-scientist","title":"Data Scientist","company":{"id":4342,"name":"Ramp","domain":"ramp.com","url":"https://alion.io/company/ramp","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":87,"open_postings":41,"ghost_share":0,"stale_share":0.512,"repost_share":0,"time_to_fill_p50_days":58,"computed_at":"2026-10-26T05:57:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":137120,"max":297330,"currency":"USD","period":"year","gross":null,"usd_annual":297330},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Looker","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"dbt","optional":true},{"name":"Fivetran","optional":true}],"status":"live","first_seen_at":"2026-06-03T17:53:31Z","employer_posted_date":"2026-06-03","last_verified_at":"2026-10-26T18:32:49Z","board_verified":true,"closed_at":null,"days_open":145,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":144},"description":"About Ramp\nRamp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.\nThe problems are high-stakes, data-dense, and unforgiving.\nWe 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.\nThe median Ramp customer saves 7.5% and grows revenue 16% in their first year - far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.\nIf you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.\nAbout the Role\nWe’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.\nWhat You’ll Do\nFull stack development, building models to consume, transform, and expose data to stakeholders and production systems\n\nDrive a culture of experimental design, testing agenda, and best practices\n\nContribute 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\n\nCollaborate with P/E/D/D (product, engineering, data and design) teams to develop product roadmaps and measure success\n\nWork 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\n\nWhat You Need\nMinimum of 4 years of industry experience as a Data Scientist\n\nStrong knowledge of SQL (preferably Redshift, Snowflake, BigQuery) and how to write efficient SQL queries\n\nFamiliarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboards\n\nTrack record of shipping high quality products and features at scale\n\nAbility to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions\n\nNice-to-Haves\nExperience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hightouch or equivalents)\n\nStrong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)\n\nExperience within the payments and financial technology space\n\nFamiliarity with B2B enterprise sales cycle metrics and processes\n\nAbout Our Teams\nProduct 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.\n\nRisk & 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.\n\nGrowth 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.\n\nBenefits available to all full-time Ramp employees (Global)\nFlexible PTO\n\nCentralized home-office equipment ordering\n\nHealth and wellness stipend\n\nBudget for intra-office travel\n\nWeekly coffee stipend\n\nUnited States\n100% medical, dental & vision insurance coverage for you, with partial coverage for dependents\n\nOne Medical annual membership\n\n401(k), including employer match on contributions made while employed by Ramp\n\nFertility HRA (up to $10,000 per year)\n\nParental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay\n\nPet insurance\n\nIn-office perks: lunch, snacks, drinks, and more\n\nRelocation expense coverage to NYC or SF (if needed)\n\nCanada\nGroup medical, dental, and vision coverage through Sun Life\n\nLife, AD&D, and disability coverage\n\nFertility drug coverage (up to $4,000 lifetime)\n\nGroup Retirement Plan with employer match (RRSP + DPSP)\n\nParental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay\n\nEmployee Assistance Program and virtual care through Lumino Health\n\nUnited Kingdom\nPrivate medical insurance through Freedom Elite\n\nVirtual GP and at-home care via eMed x Livi\n\nWorkplace pension through Penfold, with salary sacrifice option\n\nParental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay\n\nReferral Instructions\nIf you are being referred for the role, please contact that person to apply on your behalf.\nOther notices\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.\nBeware 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.\nRamp Applicant Privacy Notice","description_format":"text","description_chars":5952,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Health insurance","Insurance coverage","Parental leave","Retirement plans","Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":true,"industries":["Cards & Card Issuing","Procurement & Spend Management"],"lifecycle":[{"event":"open","at":"2026-06-03T17:53:31Z"}],"visa":[],"liveness":{"score":9,"band":"cold","label":"Long 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