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Insight Data Science General Intern Interview Questions
& Process

Real candidates share what happened, how many rounds they had,
and how the experience turned out.

Based on 14 interview experiences · FREE TO READ

1.8 Rounds average
Average Typical difficulty
92.9% Positive experience

Candidate interview experiences

First-hand accounts from people who interviewed at Insight Data Science.

Showing 3 of 14
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Insight Data Science

Fellow

Research

Entry Difficult Negative experience No offer 1 round
Interview process
Recruiter call Technical screen Presentation
Interview formats
Technical Coding Presentation

I applied to the fellowship and got an interview. It was a video interview that included a coding demo. To get ready, I learned to code some machine learning models in Python. I could explain my code to the interviewer easily enough, though I was a bit hard on myself. I also pitched a project idea for the fellowship, which the interviewer liked. Overall, I felt the interview went okay, even though I didn't really connect with the interviewer. I wasn't selected for the program and I'm not sure why.

Confirmed questions4 questions
  • Could you tell me about the statistical models you've utilized in your research?
  • Can you walk me through one of the statistical models you've used?
  • Have you worked with longitudinal data analysis before?
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Insight Data Science

Intern

Engineering

Intern Average Positive experience Decline offer 3 rounds
Interview process
Phone screen Technical screen Onsite
Interview formats
Behavioral Technical Coding

First, we had a phone screening where we talked about your background, experience, and why you're interested in this role. Then, there was a technical assessment to check your skills, usually with coding or problem-solving tasks. Finally, a more in-depth interview with the hiring manager, focusing on behavioral questions and how you could contribute to the team.

Confirmed questions1 question
  • Could you explain why you'd choose oversampling or undersampling over other methods for rebalancing data?
Insight Data Science logo
Insight Data Science

Fellow

Research

Entry Easy Positive experience Accept offer 2 rounds
Interview process
Recruiter call Technical screen Offer
Interview formats
Behavioral Coding

I applied early and had a two-stage online interview process. The first stage was a short, informal 15-minute chat about my PhD and why I'm interested in data science. The next day, I got an email asking me to prepare a code sample showcasing my data science skills for the second interview, which was a few days later. During the second interview, I shared my screen to present my code and we discussed it for about 20 minutes. I got an offer the day after that.

Confirmed questions1 question
  • Can you discuss your background and research?

Insight Data Science General Intern Interview Questions

Quoted word for word from Insight Data Science interview reports.

What would you do if you had access to all the data in existence?

Read reports

Can you identify any interesting patterns within a large volume of Yelp data?

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Could you explain why you'd choose oversampling or undersampling over other methods for rebalancing data?

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As a data scientist, what company would you like to work for?

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What's driving your desire to move from academia into data science?

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How would you apply Data Science in a business setting?

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Formats, difficulty and experience

Across all 14 Insight Data Science interview reports.

Interview formats

Technical 35.1%
Behavioral 29.7%
Presentation 18.9%
Coding 13.5%
System Design 2.7%

Interview difficulty

Easy 28.6%
Average 57.1%
Difficult 14.3%

Candidate experience

Positive 92.9%
Negative 7.1%