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ATB Financial Data Scientist Interview Questions

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

21questions
~3htotal time
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1
Product SenseStart here. 5 questions · ~44 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 valueAATB Financial
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2
A/B Testing & Experimentation4 questions · ~35 min
Design Test for New FeatureMedium

Design an A/B test for a new platform feature, including success metrics, power, guardrails, and a clear ship decision.

experiment designfeature evaluationA/B TestingAATB Financial
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 MismatchAATB Financial
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3
Behavioral & Leadership5 questions · ~44 min
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4
More topics7 questions · ~61 min
SQL Window Functions Moving AverageMedium
Practice

Calculate a three-day moving average of active-client revenue using aggregation and SQL window functions.

Window FunctionsData AnalysissqlAATB Financial
Statistical Significance in Hypothesis TestingEasy

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

Hypothesis TestingData AnalysisStatistical SignificanceAATB Financial
First Checks for Metric DropsEasy

Outline the first checks to diagnose a sudden drop in a core product metric, starting with data quality, scope, and decomposition.

Lagging IndicatorsLeading IndicatorsDiagnosisAATB Financial
Preventing Model OverfittingMedium

Tests your approach to reducing overfitting in machine learning models.

Machine LearningModel EvaluationoverfittingAATB Financial
Investigate User Engagement DeclineMedium

Investigate a 15% engagement decline by decomposing the metric, isolating root causes, and proposing actions.

RetentionDiagnosisEngagement MetricsAATB Financial
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Hands-on SQL practiceWrite and run real queries in the editor. 2 drills · ~20 min
Running Average With Window FunctionsEasy
Practice
Practice drill

Calculate each Hinge user's 30-day rolling average of daily interactions using CTEs and window functions.

Window FunctionsData AnalysissqlHingeCCatalyst Operations & AnalyticsAAlight Solutions
Using SQL Window FunctionsMedium
Practice
Practice drill

Calculate three-day rolling passenger entry averages for TfL stations using aggregation and window functions.

Window FunctionsData AnalysissqlTransport for LondonThe Trade DeskMercari
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