Data Scientist Interview Questions
Machine learning, statistics, and data analysis questions
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How would you approach A/B testing for a new recommendation algorithm?
Sample Answer:
I'd start by defining clear hypotheses and success metrics, design the experiment with proper randomization and sample size calculation...
Explain a machine learning project you've worked on from start to finish
Sample Answer:
I worked on a customer churn prediction model. We started with EDA, engineered features, tried various algorithms, and deployed using MLOps best practices...
How do you handle imbalanced datasets?
Sample Answer:
There are several techniques: SMOTE for oversampling, undersampling majority class, cost-sensitive learning, or using ensemble methods...
What's your process for feature engineering?
Sample Answer:
I start with domain understanding, then EDA to identify patterns, create interaction features, handle missing values, and validate with cross-validation...
How do you communicate technical findings to non-technical stakeholders?
Sample Answer:
I focus on business impact first, use visualizations to tell a story, avoid jargon, and provide actionable recommendations...
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