There is a lot of work and you work hands-on with their products.
Unlike some internships, where the underlings send faxes and grab coffees, Tesla interns work on real products that will be used by the world. While lots of my classmates were working on amazing technologies in their summer interships, these were all prototypes that didn’t make it into production during the internship time. At best, these projects would serve as an inspiration for new projects which would begin again from scratch. At Tesla, I was able to get my code running in production, with a direct pipeline to requests from actual customer-facing applications.
Each intern develops differentiated analytical skills and increase communication abilities while working hands-on projects with Tesla engineers. The ability to work with engineers within the company is fantastic, because it expands your personal network as the days pass by. I was able to take ownership of the entire server, and push tasks into production, things that aren’t common even for full-time employees in software giants. I got to actually think about algorithms and analytics, to the point of using an algorithm straight from an academic publication. It is true that you take from the internship what you put on it. Tesla has lots of projects and works and it is also true that there are plenty of opportunities to grow there.
Furthermore, as a data scientist at Tesla, you have access to Petabytes of data (1 Petabyte as much data as is transferred when viewing HDTV for about 13.5 years). It can be overwhelming if you try to make sense of it all at once. I have rather found it really useful to start out simple, get initial results and then iteratively improve my models. I learned that it is absolutely essential to define what your goals are before you start developing the project. This helps you direct your efforts and evaluate tradeoffs between accuracy and computation time/cost better.
Even though my focus was mostly on Computer Science stuff, the breadth of skills required to handle various steps from parsing data to interpreting the final results is very wide. Data Science is really a blend of Computer Science, Statistics, Machine Learning and some domain expertise depending on specific application (Sociology, Economics, Physics and the like). I had the opportunity to help my colleagues with the subjects I am strongest in (which doesn’t mean much in comparison with Tesla workers), and I also learned from others about subjects that I lack “expertise”.
Networking opportunities are also a big plus. Whether or not you plan to work in the auto industry in the future, interning at Tesla gives you a huge opportunity to get to know some of the most talented people in the world and to make friends with colleagues that can help you in future business or in your life. Some of the interns by themselves are already very impressive, senior employees were just like gods to our eyes.
All in all, it was a great experience interning at Tesla as a data scientist.