# 50 Data Science Interview Questions

3 min readApr 11, 2022

I needed this list of questions when I was interviewing for data science or ML engineering roles. This list aim to help data science leaders interview DS/ML engineers and help DS/ML engineers to study what is important and ace their interviews.

- What is the difference between supervised and unsupervised learning?
- What is the difference between regression, classification, clustering and ranking?
- What metrics will you use to evaluate a regression problem?
- What does it mean to have low MAE and high MSE?
- What metrics will you use to evaluate a classification model?
- Why is accuracy a bad metric for classification?
- How can you tackle data imbalance?
- Can you describe a situation where precision is more important than recall and F-score?
- Is F-score a statistically significant metric?
- Can you explain what is the area under ROC Curve (AUC-ROC)?
- Is AUC_ROC immune to data imbalance?
- What is the area under the PR curve (AUC_PR) metric?
- How will you measure the association/correlation between two numerical variables?
- How will you measure the association/correlation…