Peak Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 18 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Peak.
Peak
Data Scientist
Senior Average Neutral experience Decline offer 4 rounds
Interview process
Recruiter call Phone screen Presentation Onsite Offer
Interview formats
Behavioral Presentation Technical
It was a pretty standard interview process, with some interesting tasks and nice interviewers. First, there were a couple of phone (video call) interviews covering my background, experience, interests, and knowledge of Peak. Then, I had an on-site interview where I gave a presentation about a data science project and answered questions. The last step was a video call with the CEO. Everyone was really friendly, and the company seemed exciting, so overall it was a pretty good experience. However, after receiving an offer that was lower than I expected based on our previous talks, they stopped responding, and I haven't heard back since.
Confirmed questions1 question
- Could you share some examples from your previous work for the video calls?
Peak
Data Scientist
Mid Average Positive experience Accept offer 4 rounds
Interview process
Recruiter call Phone screen Presentation Onsite
Interview formats
Behavioral Technical Presentation
It was a 4-step process. First, a chill phone call with recruitment to introduce the company. Then, a video call with two Data Scientists where they asked about me, my background, experiences, and a few technical questions. Next, a more intense video call and presentation with three senior Data Scientists. I had to give a 20-minute presentation on a past data science project, followed by technical, general, and scenario-based questions. Finally, an in-person meeting with a Board/Exec member, which was very casual, covering general work questions and giving me a chance to ask my own. The whole thing felt fair, and I enjoyed the presentation and meeting everyone.
Confirmed questions2 questions
- Can you elaborate on an algorithm you mentioned?
- Regarding a project on retail customers, what data would be necessary?
Peak
Data Scientist
Entry Easy Neutral experience Accept offer 4 rounds
Interview process
Recruiter call Technical screen Presentation Background check
Interview formats
Technical Presentation Behavioral
The interview process starts with an initial call just to get a feel for whether or not a talent team member will progress your app. First round: You'll be with two team members and asked to talk about a topic or answer DS-relevant questions (might get your generic "explain k means clustering" Qs here). Second round: asked to give a presentation on a DS project you've worked on, maybe some technical questions on it. Will be a more senior member of the team present (two in my case, and two more DS). Culture fit: pass all the technical stuff and this will be a meeting with a non-technical team member, to talk about you, how you see yourself fitting in, whether or not you're right for the company.
Confirmed questions1 question
- Can you describe a data science project you've previously undertaken?
Peak Data Scientist Interview Questions
Quoted word for word from Peak interview reports.
“Could you explain the random forest algorithm?”
Read reports →“Could you explain the differences between XGBoost and LightGBM?”
Read reports →“Could you elaborate on the distinctions between Logistic regression and linear regression?”
Read reports →“Can you explain <insert algorithm> simply?”
Read reports →“What are your methods for evaluating a classification model?”
Read report →“Can you elaborate on Principal Component Analysis and logistic regression?”
Read report →“Could you explain a specific model (model x) in simple terms?”
Read report →“Regarding a project on retail customers, what data would be necessary?”
Read report →“Are you world class?”
Read report →Formats, difficulty and experience
Across all 18 Peak interview reports.