Data Science applicants have rated the interview process at Tesla with 3.3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 39% positive. To compare, the company-average is 55% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Science roles take an average of 36 days to get hired, when considering 18 user submitted interviews for this role. To compare, the hiring process at Tesla overall takes an average of 33 days.
Common stages of the interview process at Tesla as a Data Science according to 18 Glassdoor interviews include:
Phone interview: 22%
One on one interview: 15%
Skills test: 13%
Background check: 11%
Group panel interview: 11%
Presentation: 11%
IQ intelligence test: 7%
Personality test: 4%
Other: 4%
Drug test: 2%
Here are the most commonly searched roles for interview reports -
I applied through college or university. I interviewed at Tesla in Dec 2017
Interview
This was a phone Interview. The interview was supposed to be with 2 people - but they forgot to do a conference call and each of them ended up calling me individually. I put both of them on conference on my phone and proceeded. It went pretty well, asked about my experience, a few SQL questions, a few python questions and one question on the remanufacturing data - something like an on the spot case study. After the interview felt good and positive about it, however - a week went by , 2 weeks went by - and despite mailing the HR twice, no on bothered to get back and atleast inform about the reject.
I found the staff and the process highly unprofessional.
Interview questions [1]
Question 1
Case study related question about remanufacturing data - and how one can ensure if a part that has been gotten back for remanufacture should not defect again - using the data
A connection from my university introduced me to a team member at Tesla, leading to an interview opportunity. The process included a technical phone screen followed by an onsite round where I faced a challenging anomaly detection question about vehicle sensor data. Interestingly, I had practiced a similar scenario on PracHub just a week prior, making the technical discussion feel familiar. While I received an offer, I ultimately declined due to personal reasons. Overall, it was a tough, yet insightful experience that pushed my skills to the limit.
Interview questions [1]
Question 1
Design an anomaly detection approach for vehicle sensor time-series data, including how you would handle drift and choose a threshold.
The interview process included an initial application submission, a recruiter screening call, a technical interview focused on coding and problem solving, and a final round discussing experience, teamwork, and fit for the role.
This is strictly online, with no in-person components at all. The questions are fairly simple and straightforward. I previously completed a typing test and several other online "exams" to take as part of the process.