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10,899 data sciences interview questions shared by candidates

Here are some common data science interview questions, categorized into technical and behavioral types: Technical Interview Questions Explain the types of data science problems and the datasets used for each problem.​ What are the common issues in raw datasets that require cleaning?​ What are the different learning mechanisms in data science (supervised, unsupervised, reinforcement learning)?​ Why is standard deviation often preferred over variance when analyzing data?​ What is the difference between overfitting and underfitting, and how do you combat them?​​ What is the role of activation functions in machine learning models like linear regression and logistic regression?​ What is a confusion matrix? Describe a situation where a false positive is more important than a false negative, and vice versa.​ How do you handle imbalanced data?​ Explain the p-test and its significance in hypothesis testing.​ What is the bias-variance trade-off?​ How do you ensure that the sample chosen for a study truly represents the entire population?​ How do you handle missing values in a dataset?​ What is the goal of A/B testing?
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Data Science

Interviewed at Sahana

4★
Dec 4, 2025

Here are some common data science interview questions, categorized into technical and behavioral types: Technical Interview Questions Explain the types of data science problems and the datasets used for each problem.​ What are the common issues in raw datasets that require cleaning?​ What are the different learning mechanisms in data science (supervised, unsupervised, reinforcement learning)?​ Why is standard deviation often preferred over variance when analyzing data?​ What is the difference between overfitting and underfitting, and how do you combat them?​​ What is the role of activation functions in machine learning models like linear regression and logistic regression?​ What is a confusion matrix? Describe a situation where a false positive is more important than a false negative, and vice versa.​ How do you handle imbalanced data?​ Explain the p-test and its significance in hypothesis testing.​ What is the bias-variance trade-off?​ How do you ensure that the sample chosen for a study truly represents the entire population?​ How do you handle missing values in a dataset?​ What is the goal of A/B testing?

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