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Updated weekly · Last refresh Aug 30

Mirakl Data Scientist Interview Questions

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

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1
Machine LearningStart here. 15 questions · ~128 min
Bias-Variance Tradeoff in PracticeMedium

Explain the bias-variance tradeoff and how it guides model choice, regularization, and generalization performance.

Cross-ValidationBias-Variance TradeoffRegularizationMirakl
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2
Statistics & Probability3 questions · ~26 min
Evaluating Observed Lift SignificanceMedium

Explain how to test whether an observed experiment lift is real using hypothesis testing, p-values, and confidence intervals.

Confidence IntervalsStatistical SignificanceP-ValuesMirakl
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3
NLP3 questions · ~26 min
Transformer Embeddings vs TF-IDFMedium

Evaluates your understanding of embedding quality and tradeoffs for text similarity.

Language ModelsWord EmbeddingsTF-IDFMirakl
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4
Behavioral & Leadership17 questions · ~145 min
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5
More topics8 questions · ~68 min
Cohort Conversion ComparisonMedium
Practice

Compare Mirakl buyer cohort conversion rates using aggregation, a LEFT JOIN, and RANK window functions.

Window FunctionsCohort AnalysisAggregationsMirakl
Diagnose a Metric Drop After LaunchMedium

Investigate why a key KPI moved the wrong way after a product change and separate signal from noise.

Lagging IndicatorsLeading IndicatorsDiagnosisMirakl
Common Experimentation PitfallsMedium

Tests awareness of threats to validity and how to mitigate them in experimentation.

Network InterferenceNovelty EffectSample Ratio MismatchMirakl
Imbalanced Multi-Class EvaluationMedium

Tests your model evaluation strategy for long-tail, imbalanced multi-class problems.

Evaluation TechniquesClassificationF1 ScoreMirakl
Primary Metric DesignHard

Evaluates your product thinking and ability to translate a Mirakl feature into a measurable success metric.

MetricsUse CasesProduct VisionMirakl
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Hands-on SQL practiceWrite and run real queries in the editor. 2 drills · ~20 min
SQL Rolling Average with WindowsMedium
Practice
Practice drill

Use PostgreSQL window functions to compare Harnham Recruiter Cloud's seven-day application average with the prior week.

Window FunctionsLag/LeadRunning TotalsHarnhamHach
User Ride Trends with WindowsMedium
Practice
Practice drill

Use monthly aggregation and LAG to measure each rider’s completed ride trend and month-over-month change.

Window FunctionsLag/LeadRunning TotalsDidi ChuxingUber
The finish line: interview-readyComplete all 46 questions plus 2 hands-on drills to finish this plan.