Decimal Point Analytics Data Scientist Interview Questions
The questions to prepare for a Decimal Point Analytics Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Calculate three-day rolling user activity averages and classify behavior trends with SQL window functions.
Assess whether a new feature changed user engagement using a clear metric definition, comparison design, and guardrails.
Explain how to establish statistical significance in A/B tests using hypotheses, power, confidence intervals, and safeguards against false positives.
Framework for choosing a feature's primary success metric and guardrails before launch.
Assesses your understanding of convolutional neural networks and their core mechanics.
Diagnose a sudden 20% KPI decline by validating measurement, decomposing drivers, and separating real behavior changes from data issues.
Explain how to profile, clean, and standardize missing or dirty data before analysis.
Evaluates your ability to translate core Python and ML knowledge into a complete, practical project.
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Optimize a slow PostgreSQL query that aggregates completed transactions while preserving customers with no matching activity.
Capgemini
NomuraReplace missing sales fields with defined defaults and return a consistently ordered dataset.
University of Minnesota
The Home Depot
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