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Updated weekly · Last refresh Aug 30

Nasdaq Data Analyst Interview Questions

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

19questions
~3htotal time
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1
Behavioral & LeadershipStart here. 15 questions · ~120 min
Using Data Under AmbiguityMedium

Tests data-driven problem solving in ambiguous situations, with emphasis on ownership, stakeholder alignment, and measurable business impact.

CommunicationProblem SolvingOwnershipNasdaq
Presenting Analysis to Non-Technical LeadersEasy
Recently asked

Tests whether you can translate complex analysis into a clear, decision-oriented story for non-technical stakeholders.

Stakeholder ManagementCommunicationstarNasdaq
Building and Deploying ML ModelsMedium

Tests end-to-end ML experience including deployment considerations and practical impact.

backgroundMachine LearningNasdaq
Detecting Fraud with AIMedium

Tests understanding of applying AI to fraud detection in market transaction data.

fraud detectionNasdaq
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2
More topics4 questions · ~32 min
Integrating Multiple Data SourcesEasy

Common pipeline issues when combining multiple data sources, including schema mismatch, data quality, orchestration, and duplicate handling.

ETLData ModelingQualityNasdaq
Optimizing Slow SQL QueriesHard

Tests SQL performance tuning and data handling for high-volume market data at Nasdaq.

large datasetsperformancequery optimizationNasdaq
Automating Data ExtractionMedium

Tests automation skills and practical use of Python or Matlab for data extraction.

ToolsAutomationdata extractionNasdaq
Left vs Inner JoinEasy

Assesses your understanding of SQL join semantics and when to use each join type.

JoinssqlNasdaq

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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
Rolling 30-Day Trading VolumesMedium
Practice
Practice drill

Use a CTE and window function to calculate 30-day trading volume for active Nasdaq Trade Management accounts.

Window FunctionssqlNasdaqBinance
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

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

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
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
The finish line: interview-readyComplete all 19 questions plus 3 hands-on drills to finish this plan.