Pay
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
New York, NY (HQ) · San Francisco, CA · New York City, NY, USA
Live, first seen by us 83 days agoLocation type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: DataFrom the employer’s posting
Build full-stack models that transform and expose data to stakeholders and production systems
Design experiments and testing agendas and set best practices
Develop financial insights with Finance teams to influence business decisions
Work with data engineers to capture, move, store, and transform raw data
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
Collaborate with Finance teams (e.g. GTM Finance, StratFin) to develop financial insights and influence business decisions
Work closely with data engineering teams to capture, move, store, and transform raw data into highly actionable insights
Ability to thrive in a fast-paced, constantly improving, start-up environment that focuses on solving problems with iterative technical solutions
Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hightouch or equivalents)
Familiarity with financial metrics and processes (e.g. contribution profit, financial statements, monthly close) and / or B2B enterprise sales cycle metrics and processes
Familiarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboards
Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery) and how to write efficient SQL queries
Experience partnering with finance teams or within the payments and financial technology space
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends.
In the employer’s words · Read in context · Company website ↗
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$118K–$193K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,721 postings in the last year. Stated ranges, not salaries paid.
Day 83
Up longer than most. Similar jobs usually come down between day 7 and day 55.
From 9,988 similar postings that came down. Coming down is not always a hire.
4 open jobs
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Familiarity with financial metrics and processes (e.g. contribution profit, financial statements, monthly close) and / or B2B enterprise sales cycle metrics and processes - Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery) and how to write efficient SQL queries Nice-to-Haves
Nice-to-Haves - Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hightouch or equivalents) - Familiarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboards
- Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hightouch or equivalents) - Familiarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboards - Strong intuition on business strategy and customer empathy (ROI, growth channels, sales cycles, customer incentives)
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We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Ramp 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.
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 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.
If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
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 Finance teams (e.g. GTM Finance, StratFin) to develop financial insights and influence business decisions
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
Minimum of 3 years of industry experience in Data Science / Software Engineering / Finance
Strong AI proficiency as a lever to quickly adopt new skills and subject matter
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
Familiarity with financial metrics and processes (e.g. contribution profit, financial statements, monthly close) and / or B2B enterprise sales cycle metrics and processes
Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery) and how to write efficient SQL queries
Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Hightouch or equivalents)
Familiarity with BI tools (preferably Looker, Omni, Sigma, Hex or equivalent) and experience distributing data insights via reports and dashboards
Strong intuition on business strategy and customer empathy (ROI, growth channels, sales cycles, customer incentives)
Strong perspective on analytics engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development)
Experience partnering with finance teams or within the payments and financial technology space
Flexible PTO
Centralized home-office equipment ordering
Health and wellness stipend
Budget for intra-office travel
Weekly coffee stipend
100% medical, dental & vision insurance coverage for you, with partial coverage for dependents
One Medical annual membership
401(k), including employer match on contributions made while employed by Ramp
Fertility HRA (up to $10,000 per year)
Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay
Pet insurance
In-office perks: lunch, snacks, drinks, and more
Relocation expense coverage to NYC or SF (if needed)
Group medical, dental, and vision coverage through Sun Life
Life, AD&D, and disability coverage
Fertility 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 pay
Employee Assistance Program and virtual care through Lumino Health
Private medical insurance through Freedom Elite
Virtual GP and at-home care via eMed x Livi
Workplace pension through Penfold, with salary sacrifice option
Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay
If you are being referred for the role, please contact that person to apply on your behalf.
Pursuant 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.
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New York City, NY, USA
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