- Design, run, and analyze A/B tests and multivariate experiments, including sample size and power calculations, randomization, guardrail metrics, and interpretation.
- Apply causal inference techniques to estimate the impact of marketing campaigns, promotions, pricing, and loyalty initiatives when randomization is not possible.
- Measure and optimize marketing performance, including incrementality, attribution, ROI/ROAS, customer lifetime value, and marketing mix modeling.
- Translate business questions from growth and marketing teams into well-defined analytical problems and experimental designs.
- Develop analyses, features, and models on Databricks using notebooks, Spark, and Delta Lake.
- Collaborate with Data Engineers and Analytics Engineers on data pipelines and analytical datasets.
- Build predictive and segmentation models for churn, propensity, and customer segmentation to support targeting and personalization.
PythonSparkA/B testing+2 more