causaLens Interview Questions
The questions to prepare for causaLens interviews, across all roles. Questions from real interview reports rank first. Updated daily.
Tests conflict resolution in technical disagreements, including communication, influence without authority, and ownership of the final outcome.
Explain window functions and calculate a rolling average for time-series measurements.
Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.
Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.
Define a meaningful engagement metric for a retail analytics mobile application and explain how to validate it.
Compare Ridge and Lasso mathematically, then select between dense shrinkage and sparse feature selection based on data structure.
Describe an A/B test you ran, what question it answered, how you measured success, and what you learned from the results.
Explain how to detect, classify, and safely handle missing values in PostgreSQL production datasets.
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Calculate each user's daily and cumulative Reddit comment count, including dates with no activity.
RedditCalculate a rolling average of order values per Zomato user using a window function.
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