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"The questions you are asked in an interview for a position as a scientist will depend greatly on field of science you intend to work in. Generally, interviewers will be interested in your formal education, field of study and specialization, work, internship, and research experience, scientific writing skills, and interest in the subject matter. Expect to be asked technical questions that pertain to the knowledge needed to perform the duties of the job. While there are some positions open to scientists who possess associates' or bachelors' degrees, most jobs will require you to have at least a masters' degree with the majority requiring you to have a doctorate."

54,205 scientist interview questions shared by candidates

The data challenge is pretty standard, give you a data set and let you build a predictive model and put together some insights. Phone and onsite interviews are all technical interviews. Some statistics (sampling, hypothesis testing, power calculation, etc.), some product sense (whether to launch some features, why some metric changed, etc.), also a CS-like question.
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Data Scientist

Interviewed at Asana

4.1★
Dec 10, 2018

The data challenge is pretty standard, give you a data set and let you build a predictive model and put together some insights. Phone and onsite interviews are all technical interviews. Some statistics (sampling, hypothesis testing, power calculation, etc.), some product sense (whether to launch some features, why some metric changed, etc.), also a CS-like question.

I was asked about the way I would design the "people you may know" application of LinkedIn and about the way I would group "similar" people and jobs with people etc. More or less it was a discussion about collaborative filtering , classification and prediction models (k-means clustering, bayesian model, decision trees ).
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Analytics Scientist

Interviewed at LinkedIn

3.8★
Oct 20, 2009

I was asked about the way I would design the "people you may know" application of LinkedIn and about the way I would group "similar" people and jobs with people etc. More or less it was a discussion about collaborative filtering , classification and prediction models (k-means clustering, bayesian model, decision trees ).

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