Dataford
Top 40
Prep plan
Updated weekly · Last refresh Aug 30

Shift Technology Data Scientist Interview Questions

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

40questions
~5htotal time
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1
Machine LearningStart here. 5 questions · ~40 min
Supervised vs Unsupervised LearningEasy

Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.

Unsupervised LearningFeature EngineeringBias-Variance TradeoffShift Technology
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2
Pipelines3 questions · ~24 min
Backfilling and Incremental LoadsMedium
Recently asked

Tests your ability to design reliable data ingestion and reprocessing strategies.

Incremental loadOrchestrationBackfillingShift Technology
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3
A/B Testing & Experimentation3 questions · ~24 min
Pitfalls in Claims ExperimentsHard
Recently asked

Tests your ability to anticipate and mitigate common experimentation failures in insurance datasets.

Network InterferenceNovelty EffectSample Ratio MismatchShift Technology
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4
Product Sense4 questions · ~32 min
Finding User Pain PointsMedium
Recently asked

Tests your product discovery approach and ability to connect user needs to ML solutions.

Jobs to Be DoneUser ResearchPain PointsShift Technology
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5
Statistics & Probability3 questions · ~24 min
Train Timing ProbabilityMedium
Recently asked

Tests your probability reasoning and ability to interpret conditional timing scenarios.

probabilityExpected ValueConditional ProbabilityShift Technology
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6
Behavioral & Leadership16 questions · ~128 min
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7
More topics6 questions · ~48 min
Diagnosing Metric DropsMedium
Recently asked

Tests your debugging mindset for production metric regressions after ML deployments.

KPIDiagnosisrollout metricsShift Technology
Foreign Keys and IntegrityMedium
Recently asked

Tests your understanding of relational integrity and its impact on analytics correctness.

sql basicsnormalizationdata integrityShift Technology
Imbalanced Fraud MetricsMedium
Recently asked

Tests your ability to choose evaluation metrics that reflect real fraud detection objectives.

Evaluation TechniquesModel MetricsClass ImbalanceShift Technology
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Detect Shared Payment MethodsMedium
Practice
Practice drill

Use joins, a CTE, and HAVING to find payment methods linked to multiple Lyft user accounts.

fraud detectionsql querydata integrityLyft
Weekly Service KPI by TeamMedium
Practice
Practice drill

Analyze weekly service delivery performance by team using joins, a CTE, date aggregation, and KPI calculations.

KPIJoinssqlDeloitteReputation
Flag Suspicious Driver Signup ClustersHard
Practice
Practice drill

Use CTEs, joins, aggregations, and CASE logic to flag Lyft driver accounts with suspicious early activity patterns.

fraud detectionData AnalysisRisk ManagementLyft
The finish line: interview-readyComplete all 40 questions plus 3 hands-on drills to finish this plan.