Data Scientist applicants have rated the interview process at NVIDIA with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 55% positive. To compare, the company-average is 58.2% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist roles take an average of 49 days to get hired, when considering 11 user submitted interviews for this role. To compare, the hiring process at NVIDIA overall takes an average of 25 days.
Common stages of the interview process at NVIDIA as a Data Scientist according to 11 Glassdoor interviews include:
Phone interview: 33%
Group panel interview: 13%
Other: 13%
One on one interview: 13%
Skills test: 13%
Background check: 7%
Personality test: 7%
Here are the most commonly searched roles for interview reports -
I applied online. The process took 2 months. I interviewed at NVIDIA in Jan 2023
Interview
Overall, NVIDIA's interview process is rigorous, and candidates can expect to be tested on their technical skills, problem-solving abilities, and communication skills. It is essential to prepare thoroughly for each stage of the process and demonstrate a strong passion for NVIDIA's technology and mission.
Interview questions [1]
Question 1
Phone screen: After reviewing candidates' resumes and applications, NVIDIA's recruitment team may contact candidates for a phone screen. This interview typically lasts around 30 minutes and assesses candidates' technical background, experience, and interest in the position.
I applied online. The process took 1+ week. I interviewed at NVIDIA (Tel Aviv-Yafo) in Jan 2026
Interview
This was a technical interview . Including a leetcode question (medium) on a whiteboard and a design question . The interviewer was nice and explain the role and the demands elaborately. The
The process started with a recruiter screening where we discussed my background, the role expectations, and some logistics. The recruiter was friendly and gave me a clear idea of the next steps.
The technical round came next and included a mix of SQL, probability, and machine learning questions. I was able to answer most of them confidently, though there were a couple of curveballs—especially around feature engineering for time-series data. The interviewer was professional but a bit reserved, so it was hard to gauge how I was doing in real-time.
Conversation and questions about my prev work. I mostly talked and explained about projects i was involved with and they asked following questions. Finally one or two professional questions. Generally nice people