
Grubhub Data Scientist Interview Questions
& Process
Real candidates share what happened, how many rounds they had,
and how the experience turned out.
Based on 9 interview experiences · FREE TO READ
Candidate interview experiences
First-hand accounts from people who interviewed at Grubhub.
Data Scientist
I got contacted by the interviewer via linkedin and then we had a phone screen. The team looked like a fun group but I decided not to move forward because I had other offers that were a better fit for my interests.
- How would you compute monthly averages from a satay table?
Data Scientist
This was similar to another data science interview I had, but I'm an experienced pro with over 10 years in the field. Honestly, this interview felt super unprofessional. The interviewer was really adversarial and hostile, and sometimes didn't even seem to be listening. They'd ask something like 'explain how gradient descent works,' I'd answer, and they'd hit back with 'you didn't say the word derivative.' They also critiqued my explanation of a statistical learning method, confusing it with another method themselves. This pattern of them being wrong and trying to correct me kept happening. I tried to be diplomatic at first, but it was a lost cause. I ended the interview early because I don't want to work with hostile people. To top it off, their phone rang while I was mid-answer. Grubhub HR, please remind your interviewers that candidates should leave feeling excited, even after a tough interview. Treating candidates this way not only creates bad vibes but also loses you a customer.
- Can you define gradient descent?
- How are random forests used with categorical variables?
- Could you explain gradient boosting decision trees?
Data Scientist
I applied online. Then a recruiter reached out to me, and then scheduled two phone interviews. I guess I did not pass, as there are no follow-ups after conversation with them. I want to write this review as I found their review process a bit different from data scientist position I interviewed. Recruiters seem not professional, as she/he is the very first data science recruiter who cannot even recognize key words related to machine learning and who thinks stats and machine learning are totally unrelated. The interview is not well structured. As now I recall, the phone screens are a mixture of behavioral, technical and case interview. I do not understand how one could achieve some goals in one 30-minute interview and indeed the first interview was overtime - the interviewer obviously did not finish what he wanted to ask. I do not understand the interview order either. I was firstly interviewed by someone pretty senior before the second more junior data scientist. I felt really honored yet a bit terrified to speak with a person with such seniority for my first interview, and at the same time confused about what exactly he is looking for.
- What are your career goals and can you explain your past career moves and why you are interested in Grubhub?
- Could you share a project that you are particularly proud of?
- Could you detail your role and contributions for each of your projects, even for those that might not be your main focus?
Grubhub Data Scientist Interview Questions
Quoted word for word from Grubhub interview reports.
“How does XGboost deal with overfitting?”
Read reports →“How are random forests used with categorical variables?”
Read reports →“What's the difference between time series and XGboost?”
Read reports →“Can you define gradient descent?”
Read reports →“How would you compute monthly averages from a satay table?”
Read report →“Can you explain the difference between bagging and boosting?”
Read report →“Could you explain gradient boosting decision trees?”
Read report →“What do you think about the academic consensus on [topic]?”
Read report →“What is your understanding of fitting the residuals?”
Read report →Formats, difficulty and experience
Across all 9 Grubhub interview reports.