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Prep plan
Updated weekly · Last refresh Aug 30

Motorola Solutions Data Scientist Interview Questions

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

36questions
~5htotal time
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1
SQL & Data ManipulationStart here. 6 questions + 2 drills · ~70 min
2
Metrics5 questions · ~42 min
3
Model Evaluation4 questions · ~33 min
Assess Model Robustness and ReliabilityMedium

Approach for judging whether a model is stable, calibrated, and dependable before deployment.

PrecisionAccuracyRecallMotorola Solutions
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4
Pipelines4 questions · ~33 min
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityMotorola Solutions
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5
Machine Learning9 questions · ~75 min
Handle Highly Imbalanced ClassesMedium

Build a classifier for a highly imbalanced dataset and choose training and evaluation methods that surface rare positives.

Cross-ValidationFeature EngineeringSupervised LearningMotorola Solutions
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6
Product Sense4 questions · ~33 min
Explain Research to Non ExpertsEasy

Approach for translating a complex research result into a clear, useful message for a non-expert audience.

User NeedsValue PropositionProduct VisionMotorola Solutions
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7
More topics4 questions · ~33 min
NLP for Emergency Call AnalysisHard

Tests NLP approach for extracting signals from emergency call text and evaluating usefulness.

Language ModelsText ClassificationTokenizationMotorola Solutions
Experiment for Dispatch OptimizationMedium

Tests experimental design, causal reasoning, and evaluation of dispatch improvements for public safety use cases.

ExperimentationHypothesis TestingA/B TestingMotorola Solutions
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The finish line: interview-readyComplete all 36 questions plus 2 hands-on drills to finish this plan.