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Horizon Bank Data Scientist Interview Questions

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

Predict Loan Default for FintechEasy

Build a supervised classification model to predict 12-month loan default using credit, financial, and application features.

Cross-ValidationFeature EngineeringSupervised Learning
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Supervised vs Unsupervised Learning
Easy

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

Unsupervised LearningFeature EngineeringBias-Variance Tradeoff
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Motivation for Data Engineering Work
Easy

Explain what drives your interest in data engineering, grounded in user needs and the value created by reliable data systems.

Jobs to Be DoneUser NeedsValue Proposition
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Improve Model Accuracy SystematicallyMedium

Approach for improving a model's accuracy by checking data, features, validation, and threshold choices.

Cross-ValidationAccuracyThreshold Tuning
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Preferred Data Analysis Libraries
Easy

Explain which data analysis libraries you prefer in pipeline work and why you choose them.

ToolsData Wrangling
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Mean and Median Function
Easy

Tests your basic statistical computation skills and coding correctness.

DistributionsData WranglingExpected Value
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Structuring a Churn Analysis
Medium

Tests project framing, metric definition, data preparation, and modeling plan for churn.

KPIChurnDiagnosis
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SQL vs NoSQL Differences
Easy

Tests foundational database knowledge and when to choose each type.

JoinsData Wrangling
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