• Transform and organize complex retail transaction data, including receipt-level information and product catalog matching • Operate effectively within SQL-constrained clean room environments for data analysis and processing • Calculate incremental advertising impact on critical business metrics, including revenue and customer acquisition • Implement both experimental (randomized controlled trials) and observational methodologies • Deploy advanced causal inference techniques for longitudinal data analysis, including difference-in-differences, synthetic control methods, and variations • Apply causal machine learning approaches such as double machine learning and other innovative techniques • Design and structure controlled experiments where feasible • Create reliable causal inference frameworks for scenarios where traditional experimentation isn't possible • Translate complex technical findings into accessible insights for business stakeholders • Collaborate directly with clients to understand business context, operations, and strategic objectives • Explore and integrate novel data sources and analytical approaches to expand measurement capabilities