Own the end-to-end marketing measurement strategy across paid search, paid social, display, affiliates, CTV, and lifecycle/CRM, unifying MMM, MTA, and incrementality testing to guide channel and portfolio-level investment.
Design, launch, and analyze experiments (e.g., geo tests, PSA tests, holdouts) and causal inference studies that quantify lift, inform targeting, and establish best practices for decision-making under uncertainty.
Build and productionize predictive models (e.g., LTV, churn/propensity, audience response, budget allocation) using SQL and Python or R, partnering with data engineering to automate pipelines and ensure data quality.
Create executive-ready dashboards and narratives in tools like Looker or Mode that track KPIs, explain performance drivers, and translate insights into clear, prioritized recommendations.
Partner with Strategic Finance and Marketing leadership on forecasting, scenario planning, and quarterly planning processes; influence roadmaps and present findings to VP+ stakeholders.
Prioritize ruthlessly in a dynamic environment, managing multiple concurrent projects and elevating the team’s analytical bar through peer reviews, documentation, and mentorship.

6+ years of experience in marketing analytics or data science within technology, e-commerce, marketplace, or consumer subscription businesses.
Advanced proficiency in SQL and in either Python or R for data manipulation, statistical analysis, and modeling.
Hands-on experience designing and analyzing marketing experiments (e.g., A/B tests, geo experiments, holdouts) and applying causal inference techniques to estimate incrementality.
Proven track record implementing at least one marketing measurement approach (e.g., MMM, MTA, or structured incrementality testing) to inform budget allocation for multi-million-dollar programs.
Experience building business-facing dashboards and self-serve tools in Looker, Tableau, or Mode.
Experience working with modern data warehouses (e.g., Snowflake, BigQuery, or Redshift) and version control (Git).
Demonstrated ability to translate ambiguous business questions into analytical roadmaps and to communicate clear, actionable recommendations to non-technical and executive audiences.
Bachelor’s degree in a quantitative field (e.g., Statistics, Economics, Computer Science, Mathematics, Engineering) or equivalent practical experience.

Senior Marketing Decision Scientist

Key skills