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Tata Motors Data Science Intern Interview Questions and Answers

Updated 4 Mar 2023

Tata Motors Data Science Intern Interview Experiences

1 interview found

Interview experience
4
Good
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via LinkedIn and was interviewed in Feb 2023. There were 2 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Data Science 

(3 Questions)

  • Q1. Can you work under pressure?
  • Ans. 

    Yes, I can work under pressure.

    • I have experience working on tight deadlines and delivering high-quality results.

    • I am able to prioritize tasks and manage my time effectively.

    • I remain calm and focused in stressful situations.

    • I can adapt to changing priorities and handle multiple projects simultaneously.

  • Answered by AI
  • Q2. Where do you see yourself after 2/3/4/5 years?
  • Ans. 

    In 2/3/4/5 years, I see myself as a senior data scientist leading a team, solving complex problems, and driving impactful insights.

    • Leading a team of data scientists

    • Solving complex problems using advanced analytics techniques

    • Driving impactful insights for business decision-making

    • Continuously learning and staying updated with the latest advancements in data science

    • Contributing to the growth and success of the organizatio

  • Answered by AI
  • Q3. Why should we hire you?
  • Ans. 

    I have a strong background in data science and a passion for problem-solving, making me a valuable asset to your team.

    • I have a solid foundation in data science concepts and techniques.

    • I am proficient in programming languages such as Python and R.

    • I have experience working with various data analysis and visualization tools.

    • I am a quick learner and adapt easily to new technologies and methodologies.

    • I have excellent proble...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - We are pleased to inform you that you have been selected for an interview for the position of [Job Title] at [Company Name]. Our team was impressed with your qualifications and experience, and we believe that you would be a great fit for the role.

The interview will take place on [Date] at [Time] at our office located at [Address]. Please plan to arrive 10-15 minutes before the scheduled interview time to allow for check-in and any necessary paperwork.

During the interview, you will have the opportunity to meet with members of our team and learn more about the position and the company. You will also have the chance to ask any questions you may have about the role or the organization.

Please confirm your availability for the interview by replying to this email or by contacting us at [Contact Information]. If you need to reschedule, please let us know as soon as possible so that we can make the necessary arrangements.

Interview questions from similar companies

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I was interviewed in Mar 2024.

Round 1 - Coding Test 

45 mins 15 min mcq data science and 30 mins 1 dsa problem

Round 2 - Technical 

(5 Questions)

  • Q1. Python - All subsets of a list.
  • Ans. 

    Generate all possible subsets of a given list in Python.

    • Use itertools.combinations to generate all possible combinations of the list elements.

    • Convert the combinations to lists and store them in a new list to get all subsets.

  • Answered by AI
  • Q2. Sql query - Customers who have ordered all products from all categories.
  • Ans. 

    Use a SQL query to find customers who have ordered all products from all categories.

    • Join the Customers, Orders, and Products tables

    • Group by customer and count the distinct products ordered

    • Filter for customers who have ordered the total number of products available in each category

  • Answered by AI
  • Q3. Importance of feature engineering.
  • Ans. 

    Feature engineering is crucial in data science as it involves selecting, transforming, and creating new features to improve model performance.

    • Feature engineering helps in improving model accuracy by providing relevant and meaningful input variables.

    • It involves techniques like one-hot encoding, scaling, normalization, and creating interaction terms.

    • Feature engineering can help in reducing overfitting and improving model...

  • Answered by AI
  • Q4. Questions on project.
  • Q5. What is GAN.Have you worked with it.
  • Ans. 

    GAN stands for Generative Adversarial Network, a type of neural network used for generating new data.

    • Consists of two neural networks - generator and discriminator

    • Generator creates new data samples while discriminator tries to distinguish between real and generated data

    • Used in image generation, text generation, and other creative applications

  • Answered by AI
Round 3 - Technical 

(7 Questions)

  • Q1. Discussion on project.Demo of project.
  • Q2. Analysis sql query - whether class 11 marks or class 12 marks is greater., table given which contains student name,class,11th marks,12th marks.
  • Q3. Similar table. Find students who scored more than avg marks of both 11th and 12th.
  • Ans. 

    Find students who scored more than avg marks in both 11th and 12th grades.

    • Calculate the average marks for each student in 11th and 12th grades.

    • Compare each student's marks with the respective average marks to find those who scored higher in both grades.

  • Answered by AI
  • Q4. What is Cost function.
  • Ans. 

    Cost function is a mathematical function that measures the error between predicted values and actual values in a machine learning model.

    • Cost function helps in optimizing the parameters of a model to minimize the error.

    • Common cost functions include Mean Squared Error (MSE) and Cross Entropy Loss.

    • It is used in training machine learning models through techniques like gradient descent.

    • The goal is to find the parameters tha

  • Answered by AI
  • Q5. What is entropy.
  • Ans. 

    Entropy is a measure of disorder or randomness in a system.

    • Entropy is used in information theory to quantify the amount of uncertainty involved in predicting the value of a random variable.

    • It is often used in machine learning to measure the impurity or disorder in a dataset.

    • In thermodynamics, entropy is a measure of the amount of energy in a physical system that is not available to do work.

  • Answered by AI
  • Q6. What is ginni coefficient.
  • Ans. 

    Gini coefficient is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation's residents.

    • Gini coefficient ranges from 0 to 1, where 0 represents perfect equality and 1 represents perfect inequality.

    • A Gini coefficient of 0.4 is considered moderate inequality, while 0.6 or higher is considered high inequality.

    • It is commonly used in economics to measure income inequality with...

  • Answered by AI
  • Q7. What will happen if linear regression is used for classification
  • Ans. 

    Using linear regression for classification can lead to inaccurate predictions and unreliable results.

    • Linear regression assumes a continuous output, making it unsuitable for discrete classification tasks.

    • It may not handle outliers well, leading to incorrect classification boundaries.

    • The predicted values may fall outside the 0-1 range for binary classification.

    • Logistic regression is a more appropriate choice for classifi

  • Answered by AI
Round 4 - One-on-one 

(2 Questions)

  • Q1. Pair sum problem in python.Discussion on space time complexity.
  • Q2. Discussion on project.What algorithms used and why.

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Easy
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Campus Placement and was interviewed in Apr 2023. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. What is data science? what do you like about data science?
  • Ans. 

    Data science is a field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data.

    • Data science involves analyzing large amounts of data to uncover patterns, trends, and insights.

    • It combines statistics, machine learning, and domain knowledge to solve complex problems.

    • Data science is used in various industries such as healthcare, finance, marketing, and ...

  • Answered by AI
  • Q2. List comprehension & array related, how to reverse a list?

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
No response

I applied via LinkedIn and was interviewed in Apr 2024. There was 1 interview round.

Round 1 - Technical 

(4 Questions)

  • Q1. What is the difference between linear and classification?
  • Ans. 

    Linear regression is used for predicting continuous values, while classification is used for predicting discrete values.

    • Linear regression is used when the output variable is continuous, such as predicting house prices based on features like size and location.

    • Classification is used when the output variable is categorical, such as predicting whether an email is spam or not based on its content.

    • Linear regression aims to f...

  • Answered by AI
  • Q2. Explain example of outlier
  • Ans. 

    An outlier is a data point that differs significantly from other data points in a dataset.

    • Outliers can skew statistical analyses and machine learning models.

    • Examples of outliers include a person's weight being recorded as 1000 lbs, when the average weight is around 150 lbs.

    • Outliers can be detected using statistical methods like Z-score or IQR.

  • Answered by AI
  • Q3. Explain k mean algorithm
  • Ans. 

    K-means algorithm is a clustering technique that partitions data into k clusters based on similarity.

    • Divides data points into k clusters based on centroids

    • Iteratively assigns data points to the nearest centroid and updates centroids

    • Continues until centroids no longer change significantly

    • Example: Grouping customers based on purchasing behavior

  • Answered by AI
  • Q4. Explain the metrics for classification
  • Ans. 

    Classification metrics are used to evaluate the performance of a classification model.

    • Accuracy: measures the proportion of correctly classified instances out of total instances

    • Precision: measures the proportion of true positive predictions out of all positive predictions

    • Recall: measures the proportion of true positive predictions out of all actual positive instances

    • F1 Score: harmonic mean of precision and recall, balan...

  • Answered by AI

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Job Fair and was interviewed in May 2024. There was 1 interview round.

Round 1 - HR 

(2 Questions)

  • Q1. Introduction your self
  • Q2. What are the language you learned
  • Ans. 

    I have learned multiple programming languages including Python, R, SQL, and Java.

    • Python

    • R

    • SQL

    • Java

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - first prepare intruduction and what are languages we learned in academic .
Interview experience
4
Good
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

PYTHON,SQL,STATS,ML,DL

Round 2 - HR 

(1 Question)

  • Q1. Strenght and weakness, long term and short term goal

Interview Preparation Tips

Interview preparation tips for other job seekers - Be strong with basics and Answer confidently
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
4-6 weeks
Result
Selected Selected

I applied via Approached by Company and was interviewed in Jun 2022. There were 5 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Technical 

(2 Questions)

  • Q1. Snowflake related, database warehouse, python dataframes related
  • Q2. Power BI related questions, time intelligence, DAX, PowerBI service
Round 3 - One-on-one 

(1 Question)

  • Q1. Manager discussion, expectation setting
Round 4 - HR 

(1 Question)

  • Q1. About the company, Compensation expectation, benefits overview, relocation etc.
Round 5 - Team fit test 

(1 Question)

  • Q1. Tech stack discussion, project discussion etc.

Interview Preparation Tips

Interview preparation tips for other job seekers - Read more about data engineering, power BI time intelligence etc.
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • Q1. Python and sql connections
  • Q2. Expereience and projects
Round 2 - Technical 

(1 Question)

  • Q1. Oops concepts and sql questions
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Referral and was interviewed in Apr 2024. There were 3 interview rounds.

Round 1 - Coding Test 

Online assessment, coding mcq questions

Round 2 - Technical 

(2 Questions)

  • Q1. Use cases, resume related questions, ML related questions
  • Q2. Questions on ML algorithms, clustering, deep learning questions, should be good with at least basic concepts of ML
Round 3 - Technical 

(2 Questions)

  • Q1. Basic concepts of Ml and some valuation metrics questions
  • Q2. Customer segmentation based use case questions
Interview experience
1
Bad
Difficulty level
Moderate
Process Duration
-
Result
No response

I applied via Job Portal and was interviewed in Jul 2023. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. Previous experience, basic sql

Interview Preparation Tips

Interview preparation tips for other job seekers - The first interviewer seemed more focused on putting fake english accent rather than conducting a meaningful and professional interview.Throughout the session he incessantly blabbered in this fake english accent, which gave me headache. Instead of delving into technical job related inquiries he seemed more interested in discussing personal matters.this left me puzzled as i had prepared extensively for a discussion centered around my professional qualifications.

on the contrary the second interviewer was almost silent throughout entire process, giving off an air of disinterest. it was evident that he could not care less and his lack of engagement made the atmosphere uncomfortable. its disheartening to encounter an interviewers who shows no enthusiasm in accessing a candidates skills.

To add insult to injury at the end of the interview the interviewer with fake english accent commented on my apparent lack of energy, asking if i had not had breakfast. This comment was not only unprofessional but also completely unrelated to the purpose of the interview . it left me questioning the legitimacy of their hiring process and the professionalism of the individuals involved
according to my side i have answered all the questions they asked the interviewer also he said that will be also taking round 2 but guess he was just lying.
the experience has shed light on the toxic environment that may exist in this company because of such individuals. its even disheartening to think about the employees who had to work around these individuals regularly

Tata Motors Interview FAQs

How many rounds are there in Tata Motors Data Science Intern interview?
Tata Motors interview process usually has 2 rounds. The most common rounds in the Tata Motors interview process are Resume Shortlist.

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