Causal Inference — techniques like instrumental variables, difference-in-differences, and randomized experiments to separate correlation from cause — is core to both Economists in academia and Decision Scientists in industry building policy or business recommendations that must hold up under scrutiny. It demands a strong statistics or econometrics foundation (typically a master's or PhD), and Indian tech companies building experimentation platforms increasingly pay a premium for it over standard A/B-testing skills.
The skills most often needed alongside Causal Inference in the same roles — build these together to widen your options.
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