Energy - EV Infrastructure Data Scientist Internship (Fall 2021)

Disclaimer: This position is expected to start around August or September 2021 and continue through the entire Fall term (i.e. through December/January) or into early Spring 2022 if available. We ask for a minimum of 12 weeks, full-time, for most internships. Please consider before submitting an application.

International Students: If your work authorization is through CPT, please consult your school before applying. You must be able to work 40 hours per week. Many students will be limited to part-time depending on their academic standing. 

The Internship Recruiting Team is driven by the passion to recognize emerging talent. Our year around program places the best students in positions that they will grow both technically and personally through their experience working closely with their Manager, Mentor, and team. We are dedicated to providing an experience that allows for the intern to experience life at Tesla by given them projects that are critical to their team’s success. 

Instead of going on coffee runs and making copies, you’ll be seated at the table making critical decisions that will influence not only your team, but the overall achievement of Tesla’s mission.  

We are the team that uses data analytics to bridge the engineering, service, and deployment of Tesla’s charging infrastructure and to enhance the charging experience worldwide. 

With over 18,000 Superchargers and several thousand destination charging sites around the world, Tesla’s charging infrastructure aims to accelerate the world’s transition to sustainable transportation by enabling electric mobility without compromises. 

We use large-scale data analysis, machine learning, and modeling to retrieve actionable insights for enhancing the charging experience while minimizing the costs to Tesla. We also build the software tools and pipelines needed to maximize the leverage of these insights across our global operations. 

Intern projects may include analyzing travel and charging behavior, proposing and prototyping charging related customer experience metrics, and building models to forecast charging demand based on first principles and machine learning techniques.  

Intern will be expected to learn fast, solve problems in a fundamental way, and communicate internally and externally to drive decision making.