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Tesla Data Scientist Interview Guide

Interview Guide Apr 09

Are you interviewing for the data scientist role at Tesla? Here's an interview guide for you:

The role of a Tesla Data Scientist

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 Data Scientist Interview Guide

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.

Check out video guide that delves into the interview process and provides valuable tips tailored to each round of the interview.

Data Scientist at Tesla - Mock Interview

Schedule Mock Interview

First Screening/Recruiter round

Overview

You can expect a brief screening of 30 minutes. A recruiter will do this screening over the phone or over a video call. You can anticipate standard interview questions like "Why do you want to work at Tesla?"

You'll frequently be questioned about one particular accomplishment of which you're most proud during a Tesla interview. One of the most crucial interview questions for Tesla, so take your time. Don't undervalue this step in the process, and be sure to prepare your response in advance. Choose a scenario where you had a substantial impact on the result while answering this question. Divide it into the following sections to give a clear response:

Interview Questions

  • What was the issue?
  • What was the answer?
  • How did you resolve it?
  • What came out of it?
  • What qualities and traits are needed to work for Tesla?
  • Why do you want to work at Tesla? 
  • Where do you see yourself in the next five years?
  • What makes you a good fit for this role here at Tesla? 
  • How do you deal with tight deadlines and multiple priorities?

They will be able to tell if you were a real game-changer or merely an observer by structuring your response in this way.

Hiring Manager Round

Overview

During the hiring process for a Data Scientist role at Tesla, you will likely go through several rounds of interviews with different team members, one of them being the hiring manager. The manager will ask questions to determine if you are the right fit for the role and if you have the necessary qualifications. These questions may include inquiring about your skills and experience with specific technologies, programming languages, machine learning, data modelling, working with large data sets, data visualisation and reporting, and experience in a production setting.

During the hiring manager round, the manager will also likely evaluate your abilities in problem-solving and critical thinking, your communication and collaboration skills with cross-functional teams, your understanding of Tesla's mission, and how you can use your skills to contribute to the company's success. Your experience in identifying trends, developing new approaches, and driving advancements in data analysis will also be assessed. The hiring manager will ask for examples of your work and may ask you to explain your data analysis process and how you arrived at your conclusions. Additionally, the manager may give you a case study or data problem to solve during the interview as a way to evaluate your problem-solving and analytical skills.

Onsite Interviews for Data Scientist Role at Tesla

Overview

The onsite interview process for a Data Scientist role at Tesla typically includes multiple rounds of interviews and assessments with various members of the team.

These rounds will cover several topics. There will be technical interviews focusing on the DS craft to evaluate technical skills. You will also have discussions on past projects - which help interviewers assess your approach; your communication and critical thinking.

You will face analytics cases and business cases to understand your problem solving skills. There will be a behavioural round (often taken by one of your future teammates) to see how you'd work with others amongst others. 

The process is usually customised to the role being hired for; and the goal is to see how well your skills and experiences align to Tesla's needs and culture.

Interview Questions

  • A fair six-sided die is rolled twice. What is the probability of getting 2 on the first roll and not getting 4 on the second roll?
  • There are 100 products and 25 of them are bad. What is the confidence interval?
  • Solve exponential function and get the maximum likelihood estimator.
  • Use the “dplyr” package in R to solve a case.
  • 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
  • Reverse a string but ignore special characters
  • Reverse a linked list in-place recursively and return the new head pointer
  • Given a polynomial function with n terms and k degrees, how many partial derivatives can you form?
  • Write a command-line program to evaluate a set of equations.

Tips to Stand Out in Tesla Data Scientist Interviews

  1. Be prepared for the unexpected as the interview process will rarely follow a standard formula.
  2. Show potential to grow and think big by demonstrating how your skills and attitude can make a positive impact on the company.
  3. Emphasise your soft skills such as empathy, team work, and ability to give and receive feedback.
  4. Research the job role and the company beforehand, and come up with ideas on how you can improve the product or service you will be working on. This shows that you have invested time and effort in preparing for the interview.

Salary and Payscale - Tesla Data Scientist Role

The average salary for Top Data Scientist at Tesla is $365,326 but the range typically falls between $331,084 and $413,400. Salary ranges can vary widely depending on education, certifications, additional skills, the number of years you have spent in your profession.

Conclusion

The interview process for a Data Scientist role at Tesla typically includes multiple rounds, including a hiring manager round, technical interviews, project presentations, behavioural interviews, a meet the team session, and a business case or technical test to evaluate your problem-solving and analytical skills. The goal of the interview process is to evaluate your technical skills, problem-solving abilities, ability to communicate and work with others, and how well you align with Tesla's culture and mission. Tips for the interview include being prepared for the unexpected, demonstrating potential, showing off soft skills, and doing your homework on the role and the company. Good luck with your interview!