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Updated weekly · Last refresh Aug 30

Motorola Data Scientist Interview Questions

The questions to prepare for a Motorola Data Scientist interview. Questions from real interview reports rank first. Updated weekly.

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1
SQL & Data ManipulationStart here. 7 questions + 1 drill · ~74 min
2
Machine Learning5 questions · ~45 min
Bagging vs Boosting ExplainedMedium

Explain how bagging and boosting differ, and identify a representative algorithm for each ensemble method.

Ensemble Methodsmodel trainingSupervised LearningMotorola
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3
Behavioral & Leadership7 questions · ~64 min
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4
More topics7 questions · ~64 min
Evaluate Whether a Model Is OverfittingMedium

How to tell if a model is overfitting by comparing training and validation behavior.

Cross-ValidationAUC-ROCAccuracyMotorola
Common Pitfalls in Experiment ResultsHard

Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.

PeekingNovelty EffectSample Ratio MismatchMotorola
First Checks for Metric DropsEasy

Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.

Lagging IndicatorsLeading IndicatorsDiagnosisMotorola
Statistical Significance in Hypothesis TestingEasy

Explain what statistical significance means and why it matters when interpreting experimental or analytical results.

Hypothesis TestingData AnalysisStatistical SignificanceMotorola
Predicting Battery DegradationHard

Tests end-to-end modeling design for device health prediction and production readiness.

Motorola
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The finish line: interview-readyComplete all 26 questions plus 1 hands-on drill to finish this plan.