Tesla Data Scientist Interview Guide

Why consider Data Science Role in Tesla? 

Tesla, a leading company in electric vehicle production and one of the largest automakers in the world. Their heavy utilisation of large amounts of data to improve the autopilot features, is one of the reasons for the active recruitment of Data Scientists in Tesla. Data Scientists in Tesla are integrated into a variety of departments and jobs.

Data scientists at Tesla interact with vast amounts of data. Their analysis helps enhance the company’s autopilot features, optimise hardware designs, detect failures, and manage the electrical grid. This includes using various data visualisation tools like power bi / tableau for data analysis and collaborating with stakeholders such as engineers and managers to establish project objectives and refine the scope of analysis. Tesla’s decision-making process and initiatives are dependent on the analysis report submitted by the data scientists.

Rolds and Responsibility Taken up By Tesla Data Scientists

Data Scientists at Tesla have various responsibilities but they depend a lot on the department they are assigned to. For example, in the sales and marketing department, data scientists use data to understand customer behaviour and preferences and inform decisions related to marketing and sales strategies. Knowledge of Machine learning/Deep Learning Models can prove to be extremely useful here. Another example is the Autopilot department where image processing is extensively used. Additionally depending on the role, topics such as data optimization, demand forecasting, energy consumptions etc might be included.

Here are some examples of what a data scientist's responsibilities might include:

• Thinking of new ways of using data to improve customer delivery and service
• Working on all parts of a data project, from collecting and analysing data to creating simulations
• Talking to different teams to figure out how data can help the company
• Explaining the data well and use visual representations for better understanding
• Helping other engineers access and use data by building data pipelines
• Creating tools and measurements to help engineers use data on their own
• Writing good code that can be used and improved by other engineers.

As a Data Scientist at Tesla, you will be responsible for running and supporting your own apps in production, staying up to date on relevant technologies and suggesting new ones to the team, and using data analysis and creativity to drive advancements in current and future products.

Applying for a Data Scientist Job in Tesla

1. Go to Tesla Careers Page where vacancies will be displayed.
2. Filter out the vacancies and search for the keyword “Data Scientist.”Consider looking at related roles too, such as ML Engineer or Research Scientist.
3. Data Scientists Jobs will be displayed with the location, department, and other information.
4. Choose the required job role, it will direct you to a new web page. 
5. Click on the APPLY option and it will take you to the next step in the application process.
6. Fill out the application and the required details including your resume.

Other ways to apply:

• Networking: If you know someone who works at Tesla, reach out to them, and ask for help or a referral. One way to do this is by contacting Tesla employees on LinkedIn and asking for an informational interview. Being referred can make you stand out when applying for a job at Tesla.
• You can also try emailing a hiring manager directly instead of only filling out an application. Make sure to attach your resume. If you do not get a response, you can also apply online.

Skills and Qualifications Required

We looked at more than 60 data scientist job listings on Tesla's website and consolidated the most common requirements.

Technical Requirements

• To be a data scientist at Tesla, it is useful to have a background in computer science, mathematics or statistics.
• Hands-on experience with machine learning and deep learning techniques is considered a must-have. Strong programming skills, specifically in Python and SQL, are required. 
• Experience working with big data tools like Hadoop, Spark or Hive is necessary. 
• Knowledge of cloud computing platforms such as AWS or GCP is also pretty useful. Familiarity with data visualisation tools such as Tableau or Power BI is expected. Strong analytical and problem-solving skills, as well as strong communication and collaboration skills are required. 
• Understanding of the principles of reliability and reproducibility in data analysis is also important.

TESLA has a three-step interview process for data scientists

1. Screening/Recruiter Round: In the first round of the interview process, you will be asked to discuss your experience and accomplishments. Recruiters will evaluate your technical skills during this round. Based on our observations, recruiters typically interview around 15 candidates for each open role. However, for generalist roles or roles with multiple openings, the number of candidates interviewed may be higher.
2. Interview With Hiring Manager: If you are selected to move on to the next round of the interview process, you will be contacted by one of the hiring managers. This round typically lasts between 40-45 minutes. During this round, the hiring manager will ask you detailed questions about your professional background, with a focus on your technical skills and cultural fit. They may also talk about topics such as compensation and relocation.
3. Onsite Interviews: After successfully completing the interview with the hiring manager, you will move on to a series of on-site interviews with a panel of Tesla employees. These interviews will focus on your technical and engineering skills and how they pertain to the role you are applying for.