Data Scientist applicants have rated the interview process at DoorDash with 3.2 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 15% positive. To compare, the company-average is 35.3% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 21 days to get hired, when considering 85 user submitted interviews for this role. To compare, the hiring process at DoorDash overall takes an average of 24 days.
Common stages of the interview process at DoorDash as a Data Scientist according to 85 Glassdoor interviews include:
Phone interview: 31%
One on one interview: 26%
Skills test: 18%
Presentation: 13%
Group panel interview: 4%
Other: 3%
Drug test: 2%
Background check: 2%
Personality test: 1%
IQ intelligence test: 1%
Here are the most commonly searched roles for interview reports -
Very disengaged recruiters, did not give an idea on what to prepare for. Wasted my time preparing for 6 total rounds. I dont know what the interviewers were looking for but I did not enjoy.
Interview was 1 sql round and 1 case interview. SQL had group by, cte, lag, etc. case interview mentions a case then walking through defining success metrics, design experiment and diagnostic
I applied through a recruiter. I interviewed at DoorDash in Nov 2025
Interview
Case Study and SQL round:
Let me start by saying that I don't know yet if I am getting through to the next round.
There were no concerns about the case study section. Just that when I asked about the company culture, the first thing they said was that everyone works independently. Take what you must from that.
Next was the 30-minute live coding in SQL. There is no functionality provided to run your own code during the interview. In one of the questions, I was asked to calculate and report two metrics using two different tables. The interviewer does mention that they look for logic and not just syntax. However, expecting someone to imagine the data and perform a complex analysis does not really test the candidate's skills, only makes them nervous. One would think that, being a large company, they would be able to afford software that lets their candidates run their own code during an interview, testing their complete ability to understand data and generate insights from it. But maybe they are just looking for robots who can spew lines of code. It did not seem like an efficient way to test prospective talent.