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Hunter Douglas Data Scientist Interview Questions

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

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1
SQL & Data ManipulationStart here. 3 questions + 2 drills · ~46 min
Monthly Sales Trends by CategoryMedium
Practice

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingHunter Douglas
Contact Center Agent Performance MetricsHard
Practice
Practice drill

Compute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.

ETLAggregationsData ModelingADP
Top Customers by Net SalesMedium
Practice
Practice drill

Compute top 10 customers by net sales using joins and aggregations, ordering by revenue with deterministic tie-breaking.

SubqueriesJoinsData WranglingGain DigitalTCSZest AI
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2
Machine Learning4 questions · ~34 min
Feature Engineering for Sparse DataMedium

Explain how to engineer features for high-dimensional sparse data while controlling overfitting, dimensionality, and training cost.

data preprocessingFeature Engineeringsparse datasetsHunter Douglas
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3
Statistics & Probability3 questions · ~26 min
Stat Significance in RevenueMedium

Tests hypothesis testing and experiment/attribution rigor for revenue impact.

Hypothesis TestingStatistical SignificanceLiftHunter Douglas
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4
Behavioral & Leadership5 questions · ~43 min
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5
More topics9 questions · ~77 min
Diagnose KPI Drop After ReleaseMedium

Diagnose a post-release KPI drop by separating instrumentation issues from real behavior changes and tracing the problem through the metric hierarchy.

KPILeading IndicatorsDiagnosisHunter Douglas
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityHunter Douglas
Design Test for Novelty and SpilloversHard

Design an experiment that accounts for novelty effects and network spillovers before deciding whether to ship.

Network InterferenceExperimentationNovelty EffectHunter Douglas
CFO Margin Erosion Analysis StructureMedium

Tests analytical decomposition, prioritization, and communication of margin drivers to executives.

Hunter Douglas
Container Utilization BottleneckHard

Tests system design thinking and optimization modeling for real-world logistics constraints.

logisticsoptimizationHunter Douglas
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The finish line: interview-readyComplete all 24 questions plus 2 hands-on drills to finish this plan.