Whatnot

Data Scientist, Growth Marketing

Whatnot

full-time

Posted on:

Origin:  • 🇺🇸 United States • California, New York, Washington

Visit company website
✨ AI Apply
Manual Apply

Salary

💰 $205,000 - $240,000 per year

Job Level

Mid-LevelSenior

Tech Stack

PythonSpringSQL

About the role

  • You will be the analytical powerhouse behind our marketing initiatives, working end-to-end from data exploration to model deployment. Your work will directly influence how we invest in marketing channels, personalize user engagement, and measure ROI at scale.
  • In this role, you will:
  • Design, analyze, and interpret experiments to optimize marketing performance across channels (paid media, lifecycle marketing, influencer partnerships, etc.)
  • Build and maintain attribution models to better understand customer journeys and channel impact.
  • Develop forecasting and optimization tools to allocate budget efficiently and predict campaign performance.
  • Partner with marketing, product, and engineering teams to create data-driven strategies for audience segmentation and personalized messaging.
  • Establish scalable measurement frameworks for new marketing channels and campaigns.
  • Present actionable insights and recommendations to executive leadership in a clear, compelling narrative.
  • Team members in this role are required to be within commuting distance of our New York City, Los Angeles, Seattle, and San Francisco hubs.

Requirements

  • 4+ years of experience in data science, analytics, or applied statistics, ideally in a marketing, growth, or advertising context.
  • Advanced proficiency in SQL and Python (or R) for data manipulation, modeling, and analysis.
  • Experience with marketing measurement techniques (e.g. MMM, incrementality testing, causal inference).
  • Strong understanding of digital marketing ecosystems, including paid social, search, display, email, and affiliate channels.
  • Proven ability to design and analyze A/B and multivariate experiments.
  • Excellent communication skills, with the ability to translate complex analyses into clear, business-focused recommendations.
  • Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Economics, Computer Science, Mathematics, Engineering) or equivalent experience.