About the Role:The Marketing Data Scientist is a rigorous, intellectually curious problem solver embedded directly within the Marketing function for the GTM team. They own the science behind how we understand, attract, and grow our customers - building the models, measurement frameworks, and experiments that turn complex marketing data into decisions that move the business forward. They do not just report on what happened - they design the studies that tell us why and build the models that tell us what comes next.
What You'll Do:- Frame ambiguous marketing problems as well-scoped modeling and measurement challenges and own them end to end.
- Develop and own attribution models that accurately allocate marketing investment across channels and touchpoints.
- Build propensity, lead scoring, and churn models to prioritize where GTM teams should focus.
- Model the relationship between product engagement signals and downstream commercial outcomes - expansion, retention, and conversion.
- Design, execute, and interpret experiments (A/B, MVT, geo-based) with appropriate power analysis and statistical validity.
- Build and apply segmentation models and cohort analyses to uncover behavioral patterns, lifecycle trends, and funnel opportunities.
- Analyze organic search and AEO signals as modeling inputs to inform content strategy and improve discoverability.
- Partner with analytics engineers to productionize models and move insights from notebook to pipeline.
- Use AI tools to move faster, explore unfamiliar methods, and surface modeling options - while developing the judgment to know when AI-generated outputs are wrong or incomplete.
What You'll Bring:- Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related quantitative field; Master's or PhD is a bonus.
- 4 to 6 years applying data science in a product, growth, or marketing context at a high-growth company.
- Strong command of Python (pandas, scikit-learn, statsmodels, or similar) and analytical SQL.
- Demonstrated experience building predictive models that influenced real business decisions.
- Hands-on experience with marketing measurement - attribution, media mix modeling, incrementality testing, or similar.
- Solid statistical foundation - forecasting, regression, classification, causal inference, and experiment design.
- Experience with GA4, Google Ads, and digital marketing measurement platforms.
- Strong understanding of reverse ETL processes and operationalizing model outputs.
- Strong storytelling skills - able to translate statistical complexity into clear, actionable business language for both technical and non-technical audiences.
Bonus/Nice to Have:- Experience with MLOps practices and moving models from experimentation to production.
- Comfort working across the full stack - dbt, Hex, Snowflake, Looker, Mode, Segment, and similar tools.
- Familiarity with SaaS, developer tools, or B2B product-led growth metrics.
- Hands-on experience with AI tools like Claude, Cursor, or similar LLM-powered assistants to accelerate analytical workflows.
United States Base Pay Range
$145,000-$196,000 USD
