Dataford
Top 7
Prep plan
Updated weekly · Last refresh Sep 22
E

EarnIn Data Scientist Interview Questions

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

7questions
~1htotal time
Track your progressSign up free to work through all 7 questions and resume where you left off.
Start practicing free →
1
MetricsStart here. 1 question · ~9 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 IndicatorsDiagnosisEEarnIn
2
Product Sense1 question · ~9 min
Define Metrics for New FeaturesMedium

Define a success metric for a new feature that captures real user value, not just raw usage.

MetricsFeature Prioritizationuser valueEEarnIn

Sign up to see every question

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

Get my prep plan
3
Statistics & Probability1 question · ~9 min
Statistical Significance in Hypothesis TestingEasy

Explain what statistical significance means and why it matters when interpreting experimental or analytical results.

Hypothesis TestingData AnalysisStatistical SignificanceEEarnIn
4
SQL & Data Manipulation1 question + 3 drills · ~39 min
Handling Missing and Dirty SQL DataMedium

Explain how to profile, clean, and standardize missing or dirty data before analysis.

Data WranglingCase WhenQualityEEarnIn
Handling 30% Missing Critical DataMedium
Practice
Practice drill

Audit critical-field completeness by application source and report missing-entry percentages.

missing valuesdata accuracyData WranglingAmerican Credit Acceptance
Normalize Messy CRM Contact DataHard
Practice
Practice drill

Clean inconsistent CRM contacts by joining source tables, standardizing values, and flagging bad records.

Data WranglingCase WhenQualityAlphaSense
Validate Monthly Revenue Data QualityHard
Practice
Practice drill

Use joins, a CTE, and CASE logic to flag messy monthly order data and produce cleaned revenue by month.

Data WranglingCase WhenQualityLiterati
5
A/B Testing & Experimentation1 question · ~9 min
Common Pitfalls in Experiment ResultsHard

Identify the main pitfalls that can distort A/B test interpretation and explain how to guard against them.

PeekingNovelty EffectSample Ratio MismatchEEarnIn
6
Behavioral & Leadership2 questions · ~17 min
Handling Product Team DisagreementEasy

Tests conflict resolution, stakeholder influence, data-driven communication, and ownership during disagreement with product.

Conflict Resolutionbehavioral interviewaccountabilityEEarnIn
Leading a High-Stakes Ambiguous ProjectMedium

Tests leadership through ambiguity, ownership, and prioritization when driving a difficult project with unclear requirements and real execution risk.

CommunicationLeadershipOwnershipEEarnIn
The finish line: interview-readyComplete all 7 questions plus 3 hands-on drills to finish this plan.