Data Science Specialist Interview Questions

40,267 data science specialist interview questions shared by candidates

Three ants are sitting at the three corners of an equilateral triangle. Each ant starts randomly picks a direction and starts to move along the edge of the triangle. The probability that none of the ants collide = [ ? / ? ] Follow-up: k ants are sitting at the k corners of an equilateral polygon. Each ant starts randomly picks a direction and starts to move along the edge of the triangle. The probability that none of the ants collide = [ ? / ? ] Count how many trailing 0 in (100!)
avatar

Data Scientist

Interviewed at Meta

3.5
Jun 4, 2015

Three ants are sitting at the three corners of an equilateral triangle. Each ant starts randomly picks a direction and starts to move along the edge of the triangle. The probability that none of the ants collide = [ ? / ? ] Follow-up: k ants are sitting at the k corners of an equilateral polygon. Each ant starts randomly picks a direction and starts to move along the edge of the triangle. The probability that none of the ants collide = [ ? / ? ] Count how many trailing 0 in (100!)

Given a dataset which we cannot even see properly on hackerrank, build 2 ML models and answer insight related questions within 2 hours. It made no sense. The dataset was in raw form, had to be studied and converted into features and target, split for training/testing and report accuracy. This is not how a data science task can be completed.
avatar

Data Scientist Intern

Interviewed at Boston Consulting Group

4.2
Dec 5, 2018

Given a dataset which we cannot even see properly on hackerrank, build 2 ML models and answer insight related questions within 2 hours. It made no sense. The dataset was in raw form, had to be studied and converted into features and target, split for training/testing and report accuracy. This is not how a data science task can be completed.

Viewing 221 - 230 interview questions

Glassdoor has 40,267 interview questions and reports from Data science specialist interviews. Prepare for your interview. Get hired. Love your job.