Data Science Intern applicants have rated the interview process at Tesla with 2.5 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 70% positive. To compare, the company-average is 55% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Science Intern roles take an average of 18 days to get hired, when considering 10 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 Intern according to 10 Glassdoor interviews include:
Phone interview: 22%
Skills test: 22%
Background check: 22%
One on one interview: 11%
Group panel interview: 11%
Drug test: 11%
Here are the most commonly searched roles for interview reports -
I applied through an employee referral. The process took 3 weeks. I interviewed at Tesla in Jan 2018
Interview
3 rounds.
First round was a quick phone screening by the HR, than he gave me a project to do (a data set with two questions involving prediction / classification).
After that, a 1h interview with the hiring manager. Basic questions about motivations / resume, an easy case, and he asked me to present the project I had to do. Globally it was a pleasant interview, with a lot of a time for questions about the position.
Then I had the final round which was a 30 mn call with the director, with questions focused on my previous experience. It was also a pleasant interview.
However, after contacting them by email to let them know that I had a deadline for another offer, they did not answer me to tell me when I should expect a response...
In the first half, we discussed my background, starting with a walkthrough of my resume. My interviewer was particularly interested in my internship project at Samsung, so I spent most of the time discussing it. It was a computer vision project, so he asked some technical questions about how I implemented it.
In the second half, I did a case study. He presented a hypothetical situation where I was trying to build a customer prediction model. Given only this scenario, he asked how I would approach it. I explained what data I would collect and how I would design and train the model. He then provided feedback and questions; based on this, we discussed refining the model.
Interview questions [1]
Question 1
He presented a hypothetical situation where I was trying to build a customer prediction model. Given only this scenario, he asked how I would approach it.
I was first asked a few questions from my resume, projects and experiences. All of these were technical. Moving on, I was asked some technical questions based on the requirements mentioned in the job description.
- tell me about yourself
- tell me about the projects you have worked on
- how comfortable are you with sql and python
- why do you want to work here
- other basic statistics questions
overall pretty basic questions, but also dependent on the team