Job Description: Required Skills and Proficiency: • Proficiency in A/B testing, quasi-experiments, causal impact methods (e.g., difference-in-differences, instrumental variables, propensity scoring). • Familiarity with survival/lifecycle modeling, regression, classification, and recommendation systems. • Experience with customer journey analysis, churn prediction, subscription upsell, and personalization algorithms. • Meta-analysis across categories (pooling multiple studies while controlling for heterogeneity). • E-commerce domain knowledge: buy-box dynamics, cart abandonment, returns management, merchandising, trust signals. • Customer-centric thinking: mapping buyer journeys, satisfaction outcomes, and long-term retention vs short-term gains. • Strong SQL and data wrangling (ETL pipelines). • Proficiency with Python/R for statistical computing. • Familiarity with experimentation platforms, BI tools (Tableau, Power BI), and data warehouses (Snowflake, BigQuery, Redshift). • Prior academic research, writing and publishing experience To Apply: Share your prior research works, such as Google Scholar or ORCID