Job Description
📋 Description Design and run incrementality experiments (geo, holdout, PSA) for advertisers Build and evolve marketing mix models (MMM) and multi-touch attribution analyses Apply causal inference methods (DiD, synthetic controls, IV, propensity scoring) Translate measurement results into narratives for advertisers and product teams Partner with Engineering on data and modeling for bidding, pacing, and optimization Develop and validate predictive models to improve campaign performance 🎯 Requirements Bachelors or Masters in Statistics, Economics, Data Science, CS, or related field 3-5 years of applied data science in marketing measurement Hands-on experience designing/analyzing experiments (A/B, geo, holdout) in marketing Strong Python (pandas, statsmodels, scikit-learn, PyMC) and SQL Solid grounding in statistical inference, regression, and causal methods Ability to communicate technical results to non-technical audiences 🎁 Benefits Fully remote work environment Competitive salary and equity Performance bonuses Health, dental, and vision benefits Monthly wifi, cell phone and hardware stipend Flexible PTO and remote-friendly culture
