Data Scientist applicants have rated the interview process at Instacart with 3.1 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 38% positive. To compare, the company-average is 46.3% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 17 days to get hired, when considering 21 user submitted interviews for this role. To compare, the hiring process at Instacart overall takes an average of 16 days.
Common stages of the interview process at Instacart as a Data Scientist according to 21 Glassdoor interviews include:
Phone interview: 29%
One on one interview: 18%
Skills test: 18%
Presentation: 12%
Group panel interview: 10%
Background check: 8%
Other: 2%
Drug test: 2%
Personality test: 2%
Here are the most commonly searched roles for interview reports -
I applied through a recruiter. I interviewed at Instacart (San Francisco, CA)
Interview
I wasn't actively looking, but one of their recruiters reached out to me. I thought to myself, sure why not? We talked about the role and afterward, I felt like it was a great fit! Had a technical phone screen with one of their senior data scientists, which went very well! They followed up with a take-home assignment, which I spent two days working on, completed and sent it in. The team reviewed and decided to invite me onsite. I sent over a few days when I was available to go, but then they went quiet and didn't respond to me. After a few days of silence, I get an email from the recruiter saying that they decided to change the role completely and only look for very senior candidates.
I was speechless...
Pulling me in to go through the process, putting in the time to do the work, only to reevaluate the role entirely. Infuriating.
Interview questions [1]
Question 1
Explored various ways of monitoring user growth and retention.
Faced a deep technical challenge during the interview, asked to design a personalization algorithm for product recommendations. I walked them through feature engineering and model choices, which stressed me out initially. Luckily, I realized the structure was almost identical to a problem I had explored on prachub.com while prepping. The interview progressed through a behavioral round where they focused on my previous experiences, and I ultimately received an offer, but decided to decline after careful consideration. Overall, it was intense but rewarding.
It was pretty straightforward. HR and then technicals. The technicals were a mix of statistics and math questions. Overall, it moved pretty quickly. My interviewer was quite late with no apology and in general not very friendly. I knew someone interviewing at the same time and they had a much better experience and recieved the same questions.
Interview questions [1]
Question 1
Suppose we wanted to launch 15-minute deliveries in a specific area where we already deliver. How would you statistically test the results?