Netflix - Product-sense questions, A/B testing, experimental design, metric design Here are some examples of what we have noticed about some companies' data science interviews.Īirbnb - Product heavy, metrics diagnostics, metrics creation, A/B testing, tons of behavioral questions, and take-home material.
Some companies are very good at keeping interviews consistent, but even then, teams can deviate depending on what they are looking for. We recommend asking the recruiter if you aren’t sure which type of interview you will be facing. The other type of data science interview tends to be a mix of programming and machine learning. These are often paired with SQL and some Python questions. These interviews focus more on asking product questions like what kind of metrics would you use to show what you should improve in a product. Some data science interviews are very product and metric driven. I’ve noticed that there are several types of data science interviews that companies conduct. There are a number of subjects that need to be covered in order to ensure you are ready for back-to-back questions on statistics, programming, and machine learning.īefore we get started, there’s one tip I’d like to share. Data science interviews, like other technical interviews, require plenty of preparation.
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