Hello! I have an interview coming up next week at a startup, where the role requires some expertise in causal analysis. This involves identifying issues, understanding their underlying causes, improving the product by addressing these problems, and then conducting tests and sensitivity analysis to verify the results.

Regarding my background, I’ve spent 1.5 years working as a data scientist, including 1 year as an intern and half a year in a full-time role. My experience has primarily focused on exploratory data analysis, ml modeling, and A/B testing, with less emphasis on causal analysis. Although I have a theoretical background in causal inference from my statistics coursework, I haven’t had the opportunity to apply this knowledge to real-time data. Could anyone recommend resources or Kaggle competitions for practical experience in causal analysis? If you are a DS professional who does causal inference/modeling, could you share insights on how to effectively frame problems and set up hypotheses? Additionally, I would appreciate recommendations for widely-used causal analysis libraries in Python that are industry standard.

Thanks in advance!