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Data Scientist Interview Questions

ML, statistics, SQL, and case studies

Master the questions that data science interviewers actually ask. From ML fundamentals to business case studies—with tips on how to structure your answers.

Questions

Machine Learning

Explain the bias-variance tradeoff.

medium

When would you use a Random Forest vs. Gradient Boosting?

medium

How do you handle imbalanced datasets?

medium

Explain how a neural network learns.

hard

What's the difference between L1 and L2 regularization?

easy

How would you detect and handle overfitting?

medium

Explain cross-validation and when you'd use different types.

easy

Statistics & Probability

Explain p-values in terms a product manager would understand.

medium

How would you design an A/B test?

medium

What's the difference between Type I and Type II errors?

easy

How do you calculate sample size for an experiment?

hard

Explain Bayes' Theorem with an example.

medium

When would you use parametric vs. non-parametric tests?

medium

SQL & Data Manipulation

Write a query to find the second highest salary in each department.

medium

Explain the difference between WHERE and HAVING.

easy

How would you optimize a slow query?

medium

Write a query to find users who were active 3 days in a row.

hard

What's the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN?

easy

Case Studies

How would you build a recommendation system for an e-commerce site?

hard

How would you detect fraudulent transactions?

hard

How would you measure the success of a new feature?

medium

A model's performance dropped in production. How would you debug it?

hard

How would you prioritize multiple ML projects?

medium

Behavioral

Tell me about a time you had to explain complex analysis to non-technical stakeholders.

medium

Describe a project where your initial approach didn't work.

medium

How do you stay current with developments in data science?

easy

Tell me about a time you disagreed with a stakeholder about methodology.

medium

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Data Scientist Interview Questions

Machine Learning

Explain the bias-variance tradeoff.

When would you use a Random Forest vs. Gradient Boosting?

How do you handle imbalanced datasets?

Explain how a neural network learns.

What's the difference between L1 and L2 regularization?

How would you detect and handle overfitting?

Explain cross-validation and when you'd use different types.

Statistics & Probability

Explain p-values in terms a product manager would understand.

How would you design an A/B test?

What's the difference between Type I and Type II errors?

How do you calculate sample size for an experiment?

Explain Bayes' Theorem with an example.

When would you use parametric vs. non-parametric tests?

SQL & Data Manipulation

Write a query to find the second highest salary in each department.

Explain the difference between WHERE and HAVING.

How would you optimize a slow query?

Write a query to find users who were active 3 days in a row.

What's the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN?

Case Studies

How would you build a recommendation system for an e-commerce site?

How would you detect fraudulent transactions?

How would you measure the success of a new feature?

A model's performance dropped in production. How would you debug it?

How would you prioritize multiple ML projects?

Behavioral

Tell me about a time you had to explain complex analysis to non-technical stakeholders.

Describe a project where your initial approach didn't work.

How do you stay current with developments in data science?

Tell me about a time you disagreed with a stakeholder about methodology.

More Interview Questions

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