Tesla Research Scientist Interview Questions and Answers

Q1. Tell me about your projects?
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Q2. How do you approach the project if you are using logistic regression model?
Ans. 
Approach involves data preprocessing, model training, evaluation, and interpretation.
• Perform data preprocessing such as handling missing values, encoding categorical variables, and scaling features.

• Split the data into training and testing sets.

• Train the logistic regression model on the training data.

• Evaluate the model using metrics like accuracy, precision, recall, and F1 score.

• Interpret the model coefficients to under...read more
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Q1. What are you future goals?
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Q2. What would you do if your interested field doesnt have any work in the company?
Ans. 
I would seek opportunities to apply my skills in related fields within the company.
• Explore other departments or teams within the company that may have projects related to my field of interest

• Offer to collaborate with colleagues in different departments to bring a new perspective to their projects

• Seek out professional development opportunities to expand my skills and knowledge in related areas
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Q1. Breadth of data science, Linear algebra, prob&stats, Lin reg, Log reg, DT, RF
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Q1. Grilled in Mathematics behind Lin Reg, closed form solution, scalebility of lin reg
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Q1. System design, took a project from my resume and asked me to design the whole solution. Project was a chatbot
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Q1. Basic Recommendation System Questions
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Q2. A B Testing Questions
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Easy topics arrays, sequence sum.

Q1. SQL Window function- hard
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Q2. Case study questions answers
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Q1. Asked firstly some question over my resume then 2 case study type problems where i have to improve the recommdation system for zomato, and finally one coding question based on two pointer
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Build a simple cat and dog image classifier

Q1. ML related questions
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Q1. Behavioural questions, basically to check if you will be fit in a team
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