Top 50
Prep plan
Updated weekly · Last refresh Oct 16

Dataiku Data Scientist Interview Questions

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

50questions
~7htotal time
Track your progressSign up free to work through all 50 questions and resume where you left off.
Start practicing free →
1
SQL & Data ManipulationStart here. 7 questions + 1 drill · ~69 min
2
A/B Testing & Experimentation6 questions · ~51 min
Novelty Effects in UI TestEasy

Design a UI experiment that distinguishes short-term novelty lift from durable engagement impact under fixed traffic and guardrail limits.

ExperimentationStatistical SignificanceNovelty EffectDataiku
More A/B Testing & Experimentation questions with a free account

Sign up to see every question

Create a free account to unlock this list and practice real interview questions.

Get my prep plan
3
Metrics3 questions · ~25 min
Diagnose a Performance DropHard

Investigate whether a performance decline is seasonal or a real product issue.

Leading IndicatorsDiagnosisTime SeriesDataiku
More Metrics questions with a free account
4
Product Sense6 questions · ~51 min
Turn Feedback Into New FeaturesMedium

Approach for turning user feedback into a well-scoped feature, with clear prioritization, MVP definition, and success metrics.

User ResearchFeature PrioritizationUser NeedsDataiku
More Product Sense questions with a free account
5
Machine Learning12 questions · ~102 min
Why This Model ChoiceMedium

Evaluates your ability to justify model selection based on problem constraints and tradeoffs.

model selectionDataiku
More Machine Learning questions with a free account
6
Statistics & Probability6 questions · ~51 min
Bayesian vs Frequentist EvaluationMedium

Evaluates your understanding of frequentist versus Bayesian reasoning for model evaluation decisions.

Model EvaluationDataiku
More Statistics & Probability questions with a free account
7
More topics10 questions · ~85 min
Cleaning Missing Values in PipelinesEasy

Approach for handling missing values in a pipeline with data quality checks and repeatable transformations.

Data WranglingETLQualityDataiku
Explain Model Choice and How to ImproveMedium

Evaluates model selection reasoning and critical thinking about improvements.

model selectionfeedbackDataiku
More questions with a free account
The finish line: interview-readyComplete all 50 questions plus 1 hands-on drill to finish this plan.