Senior Data Scientist

About Ramp

At 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, Affir... (etc).

Ramp has been named to Fast Company’s Most Innovative Companies list and Linked In’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.

We’re looking for someone to help lead the future of growth  this role, you will help define the analytical frameworks and strategic roadmaps for how Ramp’s growth teams optimize and scale our marketing investments across all brand channels. You will partner closely with marketing, finance, and engineering counterparts across experimental design, statistical modeling, implementation, execution, and analysis. Our goal is to efficiently reach the right user with the right message at the right time.

Ultimately, we will depend on you to co‑own the allocation of millions of dollars per month in brand marketing spend.

• Employ statistical, machine learning, and econometric models on large datasets to evaluate channel performance and discern the causal impact of marketing and sales campaigns on a complex and nebulous enterprise sales cycle

• Build attribution models and investment frameworks to inform Ramp’s future brand channel investments, allowing Ramp’s finance and marketing teams to scale efficiently and understand which message resonates with each audience segment at each point in the customer journey

• Partner closely with Martech, Business Systems, and Growth Engineering teams to augment and leverage data across first and third‑party sources, ensuring we’ve added as much context as possible to every decision we make

• Drive experimental design and implementation on new channels and surface areas of Ramp, ensuring we can iterate quickly and cost‑effectively, especially on marketing spend designed to build awareness, consideration, and brand equity

• 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

• Bachelor’s degree or above in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields with a minimum of 5 years of industry experience as a Data Scientist

• Strong python experience (numpy, pandas, sklearn, etc.) across exploratory data analysis, predictive modeling, and applications of ML techniques to marketing‑specific problems

• Strong knowledge of SQL (preferably Snowflake, Big Query, or Redshift)

• Proven leadership and a track record of shipping improvements with growth and product organizations

• Strong perspective on the marketing experimentation lifecycle (hypothesis generation, experimental design, implementation, statistical analysis, A/B testing best practices)

• Deep familiarity with the past, present, and future of marketing attribution, martech, and the modern privacy landscape

• Ability to thrive in a fast‑paced, constantly improving, start‑up environment that focuses on solving…