Databricks Data Scientist Interview Questions
The questions to prepare for a Databricks Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Design an A/B test for a new platform feature, including success metrics, power, guardrails, and a clear ship decision.
DatabricksCompute daily active users and a 7-day rolling average using a CTE, distinct counts, and window functions.
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Compute the mean and variance of a numeric dataset from first principles.
DatabricksExplain overfitting in supervised learning and the main techniques used to improve generalization.
DatabricksExplain how to evaluate a classifier on imbalanced data, with focus on metrics that are more informative than accuracy.
DatabricksInvestigate whether a conversion drop came from product friction, traffic mix, or an experiment artifact.
DatabricksApproach for designing an end-to-end data pipeline from ingestion through transformation, storage, and downstream consumption.
DatabricksDesign a shared feature store for training and low-latency inference across many ML systems with strict freshness and consistency needs.
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