Data Scientist

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 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.