Faycal Zouine

• • Defined and led Adobe's global MMM methodology from scratch—designed hierarchical Bayesian models (PyMC3/Stan) that became the standard for measuring channel-level ROI across 6 markets, directly informing the allocation of over $250M in annual budget.

• • Presented incrementality results and budget reallocation recommendations to VP and Director-level executives in North America, Japan, EMEA, and APAC; insights shifted investment priorities and influenced go-to-market timing decisions.

• • Navigated ambiguous measurement requests from stakeholders with conflicting priorities—aligned cross-functional teams (Finance, Marketing, Regional Leads) on methodology before building models, ensuring executive buy-in on results.

• • Built customer segmentation models (K-means, DBSCAN) identifying distinct behavioral personas; results enabled Marketing to restructure campaign targeting and personalize messaging strategy by user segment.

• • Developed ARR forecasting models (ARIMA/Prophet) adopted by Finance for quarterly planning and investor communications—replaced spreadsheet-based projections with statistically rigorous and repeatable forecasts.

• • Created 2 self-serve R Shiny dashboards democratizing MMM insights—stakeholders across regions accessed ROI curves, budget scenarios, and channel performance without analyst intervention, broadening impact beyond individual requests.

• • Architected end-to-end data pipelines (SQL, PySpark, Databricks) automating ingestion, model retraining, and performance monitoring.

• • Collaborated on experiment design to measure incremental lift across digital channels.

• • Built large-scale MMMs integrating data from Google, Meta, Kantar, and affiliates—model outputs directly guided Ally Bank's media budget allocation, optimizing towards new customer sign-ups across channels.

• • Developed time-series forecasting models incorporating macroeconomic variables to predict customer acquisition for banking products (CDs, Savings Accounts); forecasts informed Ally's quarterly growth strategy.

• • Designed ML pipelines for near real-time campaign optimization; translated complex statistical results into clear recommendations for non-technical client stakeholders.

• • Led cross-functional analytics initiatives connecting data science and account teams; owned client reporting and insight delivery cadence.

• • Built econometric models forecasting vehicle sales for Nissan and Infiniti—outputs informed the strategic allocation of ~$1B in annual marketing budget across channels and regions.

• • Analyzed A/B test results to measure campaign effectiveness; findings guided optimization decisions for brand marketing initiatives.

• • Developed causal impact models quantifying the effect of external market factors on customer acquisition, supporting long-term growth planning.