
M Science Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 32 interview experiences · FREE TO READ
Which role are you interviewing for?
17 roles · 32 reportsCandidate interview experiences
First-hand accounts from people who interviewed at M Science.
Product Manager
I was ghosted after 3 rounds with no follow-up or explanation from the recruiter. This is disappointing since I heard positive feedback after each round. There was a complete lack of transparency, and I have no clue about the process or their standards. It's baffling to randomly reject candidates after multiple rounds. I'd suggest not getting your hopes up if you get an interview here.
- Could you implement a basic string function using Python?
- Can you construct a basic SQL statement?
- Could you share details about your past projects?
Software Engineer
The interview process was different than most companies, I thoroughly enjoyed each round. Minimal to no coding at all. Some system design and some IQ tests. I passed them all. I wouldn't say the interviews were difficult but they can be challenging if you don't think outside the box. However after passing all of my rounds they made me wait 5 weeks for an update. The recruiter kept leading me on telling me how overwhelmingly positive my interview feedback was. They were waiting for their #1 choice to finish their rounds most likely. I was excited to work here but their loss. I definitely think management may be questionable if it took them 5+ weeks to hire a candidate. I got through all 4 rounds in about 2 weeks for reference.
- Can you tell me what M Science does?
Data Scientist
I found the job on LinkedIn and a recruiter contacted me pretty fast. We had a phone chat about the job and what's next. Then, I had a 90-minute test with coding problems in Python and SQL, plus some Excel tasks with pivot tables. If you've used Tableau, you got an extra 10 minutes. The SQL questions were medium difficulty, and the Python problem was similar. Excel and Tableau were easy if you knew pivot tables. After the test, I talked with two quantitative analysts who asked about my background and what I'm interested in. They gave me a case study and asked what metrics I'd suggest. The last interview was with the head of product, a really nice chat, and then they made me an offer. The recruiter set up all the interviews through LinkedIn messages. It was a bit different but worked really well for scheduling compared to emails. The recruiter actually hinted before the last interview that they were likely to offer me the job.
- Given clickstream data, what metrics would you suggest to provide useful insights for media companies?
Analyst
It was a pretty standard interview process at first. I started with HR, then spoke with the head of the team, and then had interviews with some of the other analysts. Everyone I met initially was nice and seemed very capable. Things got a bit strange after meeting the CEO, who seemed unsure about what he was looking for. Because of some indecisiveness, I ended up having a few more interviews with past team members, which dragged on for about two more months. The job itself and the team seemed great, but after reading reviews about the CEO and realizing my experience wasn't unique, I decided not to accept the offer. They also offered 5% less than I expected for compensation, which felt insulting after a three-month interview process.
- Tell me about your general technical skills.
M Science Interview Questions
Quoted word for word from M Science interview reports.
“Given a couple with two children, if at least one is a daughter, what is the probability they have one son?”
Read reports →“Could you implement a basic string function using Python?”
Read reports →“Can you complete this relation in 2 minutes: If 1 maps to 2, 3 maps to 12, and 10 maps to 110, what does 250 map to?”
Read reports →“How would you distribute 52 marbles (2 red, 50 black) to have the best chance of picking the two red marbles consecutively?”
Read reports →“Regarding examples of different table/relationship types, which joins might lead to duplicate entries or infinite rows?”
Read report →“Given clickstream data, what metrics would you suggest to provide useful insights for media companies?”
Read report →“For understanding a specific industry, what data sources and metrics would be most valuable?”
Read report →“Can you construct a basic SQL statement?”
Read report →“How would you approach drawing conclusions from a hypothetical dataset?”
Read report →Formats, difficulty and experience
Across all 32 M Science interview reports.