Question 1

How should I prepare for a data science interview?

Accepted Answer

Whether you're interviewing at a top tech company like Google, Meta, or Amazon, or a growing startup, data science interviews are rigorous and typically focus on five main areas:

Coding. Expect SQL, data structure, algorithm, and modeling questions. You may be asked to write code on a virtual whiteboard and explain your logic step by step.
Statistics. You'll face questions that test your knowledge of statistics fundamentals and your ability to explain statistical concepts. Some common topics typically asked include A/B testing, probability, and statistical models.
Machine learning. Depending on the role, you may need to discuss specific ideas around system design and ML models, build a hypothetical model, or explain how you'd improve one to solve a real-world problem.
Product sense. Many interviews include product-focused questions, sometimes in the form of a case study. You may need to explain how you define metrics, run experiments, and guide product decisions.
Behavioral. Be ready to walk through your experience, how you solve problems, and why you're a good fit for the team and role.

To prepare:

Brush up on SQL, statistics, and ML fundamentals
Practice coding and case questions under time pressure
Refine your project stories and be ready to explain the impact of your work using data
Do mock interviews with an experienced data science interviewer

Read our data science interview prep guide for a more detailed breakdown of the process and question types.

Question 2

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Accepted Answer

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Question 3

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Accepted Answer

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Question 4

How much do {{page.skill.name}} mock interviews normally cost?

Accepted Answer

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Question 5

How will my {{page.skill.name}} mock interview work?

Accepted Answer

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