SoftServe 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 SoftServe.
SoftServe
Data Scientist
Mid Average Positive experience No offer 4 rounds
Interview process
Recruiter call Technical screen Onsite Background check Offer
Interview formats
Behavioral Technical Coding
So the interview had a few parts, testing both technical stuff and how I'd actually do the work. They went into my past jobs, what I used, how big the data was, how I code, and my MLOps knowledge. There were also some standard ML questions, like when to use old-school ML vs. neural nets, and deep dives into ensemble methods, boosting, bagging, XGBoost, random forests, and decision trees. They also asked about problems I'd run into and how I solved them. Got my feedback the day after.
Confirmed questions6 questions
- Can you tell me about your practical data science experience, including your previous job responsibilities, the tools you utilized, and the scale of datasets you worked with?
- Regarding your coding habits, do you write code, and if so, how do you maintain clean code practices?
- What are your capabilities in MLOps?
SoftServe
Data Scientist
Senior Difficult Positive experience No offer 3 rounds
Interview process
Recruiter call Technical screen
Interview formats
Behavioral Technical
So I had an HR interview first, then a team interview, and the final one was a technical interview. The first couple went really well, I felt like a good match. The technical interview was a bit intense, asking really specific theoretical questions that aren't that common in the industry anymore, more like stuff you'd remember from university.
Confirmed questions1 question
- Can you explain how to calculate feature importance in a random forest?
SoftServe
Data Scientist
Entry Average Negative experience No offer 2 rounds
Interview process
Recruiter call Technical screen
Interview formats
Technical
It was a pleasant experience overall. It started with a brief call with HR, followed by a technical interview. They were prompt with feedback, which was mostly constructive.
Confirmed questions1 question
- What are your thoughts on Neural Networks and activation functions?
SoftServe Data Scientist Interview Questions
Quoted word for word from SoftServe interview reports.
“When would you say classical machine learning is a better choice than deep neural networks?”
Read reports →“Can you explain how to calculate feature importance in a random forest?”
Read reports →“Can you explain k-fold cross-validation?”
Read reports →“How would you perform clustering on time series data?”
Read reports →“What are your thoughts on Neural Networks and activation functions?”
Read report →“Can you explain the working of a diffusion model?”
Read report →“What are your thoughts on boosting, bagging, XGBoost, random forest, and decision trees in general?”
Read report →“Regarding your coding habits, do you write code, and if so, how do you maintain clean code practices?”
Read report →“What are your capabilities in MLOps?”
Read report →Formats, difficulty and experience
Across all 7 SoftServe interview reports.