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Maruti Suzuki Data Scientist Interview Questions and Answers
Maruti Suzuki Data Scientist Interview Experiences
1 interview found
Anonymous
I applied via Job Fair and was interviewed in May 2024. There was 1 interview round.
(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
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Data Scientist Jobs at Maruti Suzuki
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I applied via LinkedIn and was interviewed in Apr 2024. There was 1 interview round.
(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...
- 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.
- 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
- 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...
Skills evaluated in this interview
I applied via Job Portal and was interviewed in Jul 2023. There was 1 interview round.
(1 Question)
- Q1. Previous experience, basic sql
Interview Preparation Tips
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
Selected
I applied via campus placement at Symbiosis Centre For Management and HRD (SCMHRD) and was interviewed before Jul 2023. There were 3 interview rounds.
It was campus placement. We were givien the topic "future of AI and ML in automobile industry". The time given was around 15mins. The explained the process in great detail and very clearly.
(2 Questions)
- Q1. CV and basic of ML
- Q2. What if questions. For eg, if you want to launch a new EV in market then what will be your approach What if you are the CEO.. ETC
(2 Questions)
- Q1. Ethical questions
- Q2. Besic HR questions like why this company
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- Machine Learning
- Tata motors history
- Your CV
I applied via Referral and was interviewed in Jan 2024. There was 1 interview round.
(1 Question)
- Q1. How did we solve business problems thru analytics stack
- Ans.
We utilized our analytics stack to identify patterns, trends, and insights in data to address business challenges.
Utilized data visualization tools to identify trends and patterns in customer behavior
Leveraged machine learning algorithms to predict customer churn and optimize marketing strategies
Used statistical analysis to determine the impact of pricing changes on sales performance
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Data Scientist Interview Questions & Answers
Mahindra & Mahindra
Abhijit Kundu
posted on 29 Nov 2024
Selected
I applied via Naukri.com and was interviewed before Nov 2023. There were 4 interview rounds.
(2 Questions)
- Q1. Tell me about yourself
- Q2. Questions from projects which was mentioned on resume
(2 Questions)
- Q1. Fitment based questions
- Q2. Explain a project
- Ans.
Developed a machine learning model to predict customer churn for a telecom company.
Collected and cleaned customer data including usage patterns and demographics
Used classification algorithms like Random Forest and Logistic Regression to build the model
Evaluated model performance using metrics like accuracy, precision, and recall
Math, English, reasoning
(1 Question)
- Q1. Asked me about expected salary
jaspreet kaur
Selected
I applied via Naukri.com and was interviewed before Feb 2023. There were 2 interview rounds.
(1 Question)
- Q1. What is difference between lstm and rnn
- Ans.
LSTM is a type of RNN that addresses the vanishing gradient problem by using memory cells.
RNN stands for Recurrent Neural Network, a type of neural network that processes sequential data.
LSTM stands for Long Short-Term Memory, a type of RNN that includes memory cells to retain information over long sequences.
LSTM is designed to overcome the vanishing gradient problem, which occurs when training RNNs on long sequences.
L...
(1 Question)
- Q1. What are different evaluation matrix ?
- Ans.
Evaluation matrices are used to assess the performance of models in data science.
Confusion matrix: used to evaluate the performance of classification models.
Precision, recall, and F1 score: measures for binary classification models.
Mean squared error (MSE): evaluates the performance of regression models.
R-squared: assesses the goodness of fit for regression models.
Area under the ROC curve (AUC-ROC): evaluates the perfo...
Skills evaluated in this interview
Selected
I applied via Referral and was interviewed before Oct 2022. There were 3 interview rounds.
(1 Question)
- Q1. Basic Statistics and past experience
Presentation on any fo past project
I applied via Recruitment Consultant and was interviewed in Jul 2021. There was 1 interview round.
Interview Questionnaire
3 Questions
- Q1. Project Based Questions
- Q2. Which Algorithms you used , statistical measured , challenges , outcome
- Ans.
I have used various algorithms such as linear regression, decision trees, and neural networks to analyze data and make predictions.
Used linear regression to predict housing prices based on various features
Implemented decision trees to classify customer behavior and recommend products
Utilized neural networks for image recognition tasks
Challenges included dealing with missing data and overfitting
Outcome was improved accu
- Q3. Why a specific algorithm was used. Reasoning.
- Ans.
The algorithm was chosen based on its ability to handle large datasets and its accuracy in predicting outcomes.
The algorithm was selected after evaluating its performance on similar datasets.
It was chosen for its ability to handle high-dimensional data and its scalability.
The algorithm was compared to other models and found to have the highest accuracy in predicting outcomes.
The choice of algorithm also depends on the
Interview Preparation Tips
Skills evaluated in this interview
I applied via Referral and was interviewed before Jun 2021. There were 5 interview rounds.
Python or R based coding questions
Need to present your case study in front of a panel
(2 Questions)
- Q1. Probability & Distributions
- Q2. Tech questions on your project
(1 Question)
- Q1. General discussion & Negotiation
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