Senior Manager, Data Science
Walmart
PythonSparkSQL
Data Scientist, Growth Marketing
Whatnot
full-time
Posted on:
Location: California, New York, Washington • 🇺🇸 United States
Visit company websiteSalary
💰 $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.
