What is a causal inference?

A Causal Inference job involves using statistical and computational methods to determine cause-and-effect relationships from data. Professionals in this field work with observational and experimental data to identify causal impacts, often in domains like economics, healthcare, social sciences, and technology. They apply techniques such as propensity score matching, instrumental variables, and difference-in-differences to ensure rigorous analysis. These roles are commonly found in academia, policy research, and data science teams within tech and finance companies. Strong skills in statistics, programming (e.g., Python, R), and experimental design are typically required.