If you are a recent graduate or someone preparing for your first data scientist position, then here are some tips to help you ace your interview!
Interview types:
For core data scientist roles, you will have both technical and behavioral interviews.
Some employers will have them as separate interviews, while some use the same time slot to do both. Lately a lot of initial phone screens use a combination of tech Qs apart from the traditional "resume walk-through" to narrow down the applicant list for round 2 interviews. So be prepared for some basic tech Qs even on initial phone screens with HR.
Coding interviews (using collaborative software or take home tests) are also becoming routine, but only on topics listed on your resume. So if you’ve listed Python, expected to show some coding on it. If you put R/SQL, don't be surprised if you are asked to write pseudocodes or complex joins.
The interview format itself can vary a lot, ranging from phone, teleconference, in-person, online skill tests and a combination of all. In-person interviews is usually the last round and some companies are completely eliminating onsite interviews to cut costs, especially for teams that are fully distributed across the globe.
Technical interviews:
Behavioral interviews:
Use the STAR method to answer these Qs, which will basically evaluate you on (a) Teamwork/ culture fit, (b) Communication skills, (c) Problem-solving, (d) presenting convincing “actionable insights”.
This might seem like a lot of topics, but data scientist roles are highly paid ($100k+) because these roles require a ton of specialized knowledge. That said, if you want more details on how to get interviews or prepare with a detailed list of 100+ technical and behavioral Qs asked in actual DataScience interviews, then take a look at my book - “Data Science Jobs”. This includes resources on interview Qs on ML algos/ statistics / R/Python/Tableau as well.
All the best for your job search!
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