Ramp
Senior
Co-own millions in monthly brand marketing spend with attribution and experimentation at Ramp
Ramp is hiring a Senior Data Scientist to lead analytical frameworks for how its growth team scales brand marketing investment across channels, working closely with marketing, finance, and engineering. The role centers on building attribution models, running channel experiments, and quantifying causal impact of campaigns on a long, nebulous enterprise sales cycle. Interview should probe applied ML/econometrics on marketing data, attribution methodology, and comfort owning large budget-allocation decisions in a fast-moving startup.
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What this interview tests
- Attribution modeling for complex B2B enterprise sales cycles
- Causal impact of marketing/brand campaigns on nebulous funnels
- Marketing experimentation lifecycle and A/B testing best practices
- Applied ML/econometrics in Python (numpy, pandas, sklearn) on large datasets
- Cross-functional ownership with marketing, finance, growth engineering
- Modern privacy landscape and evolving attribution/martech
Common question themes
How would you build an attribution model for a long enterprise sales cycle
Design an experiment to test a new brand channel with limited signal
Separate causal marketing impact from confounds like seasonality
How do you decide where to allocate incremental marketing budget
How has privacy/cookie deprecation changed your attribution approach
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