Glassdoor users rated their interview experience at Wildberries Marketplace as 100% positive with a difficulty rating score of 4 out of 5 (where 5 is the highest level of difficulty). Candidates interviewing for Data Scientist and rated their interviews as the hardest, whereas interviews for Data Scientist and roles were rated as the easiest.
I applied online. I interviewed at Wildberries Marketplace (Moscow, Moskva) in Mar 2025
Interview
The interview process at WB consisted of several stages: 4 interview rounds in total, plus a take-home test assignment.
The first stages were more general and focused on my previous experience, motivation, relevant projects, and basic understanding of the business analyst role. There was also a test assignment, which assessed my ability to structure a problem, work with data and logic, and formulate clear conclusions.
The last two rounds were the most substantial and each lasted around one hour. They were conducted with the Strategy Team Lead and a Senior Manager. The main focus was on testing hard skills and logical thinking. I was asked many logic-based and market-sizing questions, mostly in the guesstimate / Fermi problem format, for example: “How many yellow cars are there in Czechia?”
For these questions, the exact final number was less important than the reasoning process. The interviewers wanted to see how I structured ambiguous problems, what assumptions I made, how I broke the task down into smaller parts, and how I checked whether the final estimate made sense.
Overall, the process was quite intensive, especially during the final stages. It is important to be ready to think out loud, quickly structure unclear problems, and confidently explain the logic behind your answer.
I applied through a recruiter. I interviewed at Wildberries Marketplace (Moscow, Moskva) in Feb 2026
Interview
Asking about background, choosing couple of cases on application of ML. Follows up with theoretical and fundamental mathematical questions regarding why it happens, when it happens, why it is important. Topics are relatively depends on your background, mine was about Decision Trees, Linear regression, L1/L2, ROC-AUC, PR-AUC, TimeSeries.
Interview questions [3]
Question 1
What is the mathematical reason why it is very important to remove multicollinearity in Linear regression models and why multicollinearity does not have such impact on decision trees?
I interviewed at Wildberries Marketplace (Moscow, Moskva)
Interview
Two young guys asked questions about general ML and computer vision in particular. Questions about the number of parameters in a convolution are a bit odd for a senior position—I've only needed that 0 times in five years—but overall, they expect a broad perspective during the interview.