SMX Data Scientist Interview Questions
The questions to prepare for a SMX Data Scientist interview. Questions from real interview reports rank first. Updated weekly.
Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.
SMXTests ability to assess data quality, assumptions, and fit for modeling choices.
SMXAggregate completed SMX product sales and return the top 10 products by units sold.
SMXA framework for deciding which features should ship first when building a new product.
SMXPick the right metrics to evaluate a machine learning model and explain why they fit the problem.
SMXTests ability to frame churn problems and choose modeling and evaluation steps.
SMXTests foundational knowledge of linear regression assumptions and how they affect inference.
SMXTests understanding of robust evaluation and correct cross-validation setup.
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Calculate daily session-level funnel conversion rates using CTEs, CASE WHEN, and date functions.
Compute per-vehicle daily autonomous vs manual seconds from state-change logs using LEAD and conditional aggregation.