Develop causal economic analyses using econometric and machine-learning methods to measure business, market, and external-shock impacts. Lead projects from data ingestion and feature engineering through model validation and stakeholder communication. Guide causal inference best practices, prototype scalable analytics, collaborate with internal and external clients, and stay current with research methods. The role requires strong quantitative training, programming in Python or R, SQL knowledge, quasi-experimental methods, causal machine learning, experimentation, and clear communication to nontechnical audiences.