Chartboost 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 Chartboost.
Chartboost
Data Scientist
Senior Difficult Positive experience No offer 3 rounds
Interview process
Recruiter call Technical screen Technical screen
Interview formats
Behavioral Technical Coding
Communication was quick. My interview process included 3 rounds: first, a general chat with the recruiter. Then, a Data Science discussion with the Director of Engineering about my past projects. Finally, a live coding test on Hackerrank which had 4 questions (2 SQL, 2 Python). I had to complete at least 2 questions. The SQL questions involved writing queries with conditions. The Python question was about manipulating a tuple using a loop with conditions. I didn't get to the fourth round, which was a talk with a project manager. The role seemed to require strong coding skills, which was a bit disappointing as I see Data Science as more than just coding.
Confirmed questions2 questions
- Tell me about your previous projects.
- Discuss past projects and Hackerrank questions in SQL and Python.
Chartboost
Data Scientist
Senior Average Positive experience Decline offer 5 rounds
Interview process
Recruiter call Phone screen Technical screen Panel Onsite Offer
Interview formats
Behavioral Technical Coding Case Presentation
Recruiter reached out, and the interview process was quick and smooth. Started with a hiring manager screen about ML and my past work. Then, a coding screen focused on Python and SQL. Next, a panel interview with a peer and a senior leader discussing ML case studies. Finally, I met with the hiring manager again to talk about job responsibilities, career growth, and company culture. It was a really good experience overall. All the questions felt relevant to the job, which was helpful for me to understand the role and for them to see if I was a fit. The team members are all smart and down-to-earth. The hiring manager is super experienced and really invested in his team's development. Lots of cool projects too. The Head of Talent was also great to communicate with during the offer stage, very transparent. The pay was competitive, but I ended up choosing another company for personal reasons.
Confirmed questions1 question
- Can you explain how you would go about building a click-through rate model?
Chartboost
Data Scientist
Entry Average Positive experience No offer 6 rounds
Interview process
Recruiter call Technical screen Onsite
Interview formats
Coding Technical
Got a call from the recruiter, then had an intro with the hiring manager. The next day, the recruiter contacted me again for a coding interview. Following that, there was a virtual on-site which consisted of four interviews. The recruiter got in touch the day after that.
Confirmed questions3 questions
- Could you solve this easy Leetcode problem?
- Tell me about statistics.
- Tell me about ML.
Chartboost Data Scientist Interview Questions
Quoted word for word from Chartboost interview reports.
“What data sources might be useful for feature engineering?”
Read reports →“Could you solve this easy Leetcode problem?”
Read reports →“What's your approach to handling class imbalance in datasets?”
Read reports →“Describe the methodology for selecting a sample to test the model in a live environment.”
Read reports →“Could you describe features that could be useful for prediction?”
Read report →“Can you explain how you would go about building a click-through rate model?”
Read report →“Tell me about statistics.”
Read report →“Tell me about ML.”
Read report →“How would you approach solving problem X?”
Read report →Formats, difficulty and experience
Across all 7 Chartboost interview reports.