About Ramp

Ramp is the ultimate platform for modern finance teams. It integrates corporate cards with expense management, bill payments, vendor management, accounting automation, and more. Ramp's comprehensive solution aims to save businesses time and money, and allows finance teams to perform their best work. Our mission is to help create healthier businesses, and we are achieving it: Over 15,000 businesses using Ramp save an average of 3.5% more and close their books 8 times faster.

Established in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, supporting tens of billions of dollars in purchases every year.

Ramp's investors encompass Founders Fund, Stripe, Citi, Goldman Sachs, Coatue Management, D1 Capital Partners, Redpoint Ventures, General Catalyst, and Thrive Capital, as well as over 100 angel investors who were founders or executives of leading companies. Ramp's team includes talented leaders from major financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies like Meta, Uber, Netflix, Twitter, Dropbox, and Instacart. In 2023, Ramp was named Fast Company’s #1 Most Innovative Company in North America, a CNBC Disruptor, and a TIME100 Most Influential Company.

About the Role

We're searching for an individual to head the future of growth data science at Ramp. In this role, you will assist in establishing analytical frameworks and strategic roadmaps for Ramp’s growth teams to optimize and enhance our marketing investments across all channels. You will work closely with marketing, finance, and engineering teams on experimental design, implementation, execution, and analysis. Our objective is to reach the right user with the right message at the right time. Essentially, we count on you to develop best practices across Ramp for marketing experimentation and data-driven investment decisions.

What You’ll Do

• Use statistical, machine learning, and econometric models on large datasets to evaluate channel performance and determine the causal impact of marketing and sales campaigns on an intricate and ambiguous enterprise sales cycle.
• Develop attribution models and investment frameworks to guide Ramp’s future channel investments, enabling Ramp’s finance and marketing teams to scale efficiently.
• Work closely with Martech, Business Systems, and Growth Engineering teams to enrich and utilize data from first and third-party sources, ensuring we add as much context as possible to every decision we make.
• Design and implement experiments on new channels and surfaces areas of Ramp, enabling quick and cost-effective iterations, especially on marketing expenses intended to build awareness, consideration, and brand equity.
• Contribute to the culture of Ramp’s data team by influencing processes, tools, and systems that will enable us to make better decisions in a scalable manner.

What You Need

• Bachelor’s degree or higher in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields with at least 5 years of industry experience as a Data Scientist.
• Extensive experience with Python (numpy, pandas, sklearn, etc.) for exploratory data analysis, predictive modeling, and application of ML techniques to marketing-specific problems.
• Strong knowledge of SQL (preferably Redshift, Snowflake, BigQuery).
• Proven leadership and a track record of delivering improvements with growth and product organizations.
• Potent perspective on the marketing experimentation lifecycle (hypothesis generation, experimental design, implementation, statistical analysis, A/B testing best practices).
• In-depth familiarity with the evolution, current state, and future of marketing attribution, martech, and the modern privacy landscape, especially as it relates to B2B SaaS GTM motions.
• Ability to thrive in a fast-paced, continually evolving, start-up environment that focuses on solving problems with iterative technical solutions.

Nice-to-Haves

• Experience at a high-growth startup.
• Experience with the modern data stack (Fivetran / Snowflake / dbt / Looker / Census or equivalents).
• Familiarity with data orchestration platforms (Airflow, Dagster, Prefect).
• Strong perspective on the data science engineering development cycle (data modeling, version control, documentation + testing, best practices for codebase development).

Compensation

• The annual salary/OTE range for the target level for this role is $182,750-$215,000 + target equity + benefits (including medical, dental, vision, and 401(k).

Benefits (for U.S.-based full-time employees)

• 100% medical, dental & vision insurance coverage for you.
• Dependent coverage partially covered.
• One Medical annual membership.
• 401k (including employer match on contributions made while employed by Ramp).
• Flexible PTO.
• Fertility Health Reimbursement Account (up to $5,000 per year).
• Work from home stipend to accommodate your home office needs.
• Wellness stipend.
• Parental Leave.
• Relocation support.
• Pet insurance.