The Causal Inference Playbook: Advanced Methods Every Data Scientist Should Master

Advanced causal inference methods are presented for data scientists looking to move beyond foundational techniques. It explores techniques like Doubly Robust Estimation, Instrumental Variables, and Regression Discontinuity to address complex real-world challenges like unmeasured confounders and selection bias. Using a recurring case study of a job training program, the article explains the core intuition and requirements for each method. Practical implementation steps and Python code examples are provided to help practitioners apply these powerful tools for more credible analysis.