
Pocket Gems Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 7 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Pocket Gems.
Data Scientist
The overall process was fine. The interviewer was the director, and they're looking for folks with experience. The team itself doesn't really focus on A/B Testing; that's handled by another group in the company.
- Can you explain what a P-value is?
- What is overfitting in your own words?
- Could you describe what an AB test is?
Data Scientist
I was reached out via email and then had a phone interview the following week. The interviewer was super nice and the topics were engaging. They gave me this cool assignment that involved designing an A/B test and doing an ML categorization task. A few days after I sent it back, I got another call to go over the assignment and my past work. Then, they invited me to San Francisco for the final round. Overall, I really liked the whole thing and everyone was so friendly. Sadly, I didn't get an offer in the end.
- How would you design and execute A/B tests?
Data Scientist
Got contacted after applying and scheduled a phone interview for a week later. The interviewers wanted a self-introduction, but they weren't really interested in my past experience. Instead, they asked a case question that didn't have a clear goal or enough background info, yet they expected a very specific answer. The interviewer didn't seem to realize that the question statement itself was confusing due to bad logic, not just jargon.
- Could you outline a strategy for developing an ads bidding system and convince senior management of its profitability?
Pocket Gems Data Scientist Interview Questions
Quoted word for word from Pocket Gems interview reports.
“Can you define p-value?”
Read reports →“What is a confidence interval?”
Read reports →“Can you explain what a P-value is?”
Read reports →“Which players should we target for our new feature?”
Read reports →“Create a basic Python machine learning model to predict the likelihood of a user converting. The focus is on your model-building process, data selection for training, and target variable definition, not on extensive feature selection, engineering, or tuning.”
Read report →“What is overfitting in your own words?”
Read report →“Could you describe what an AB test is?”
Read report →“Can you discuss LTV and relevant metrics?”
Read report →“Which group of users would you pick for the promotion, and why, based on the sample data?”
Read report →Formats, difficulty and experience
Across all 7 Pocket Gems interview reports.