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Gramener Data Science Engineer Interview Questions and Answers

Updated 22 Sep 2023

Gramener Data Science Engineer Interview Experiences

1 interview found

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

I applied via Campus Placement and was interviewed before Sep 2022. There were 4 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 Resume tips
Round 2 - Coding Test 

Test based on js, python, html and css

Round 3 - Technical 

(1 Question)

  • Q1. Questions on oops concepts
Round 4 - Technical 

(1 Question)

  • Q1. Question on python, data structures

Interview Preparation Tips

Topics to prepare for Gramener Data Science Engineer interview:
  • python
  • Javascript
Interview preparation tips for other job seekers - the best place to work, friendly colleagues and helpful in each and every aspect, prepare well with the basics in all languages

Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. What friends think of you?
  • Ans. 

    My friends think of me as reliable, supportive, and always up for a good time.

    • Reliable - always there when they need help or support

    • Supportive - willing to listen and offer advice

    • Fun-loving - enjoys socializing and trying new things

  • Answered by AI

Interview Preparation Tips

Round: Resume Shortlist
Experience: After Resume Shortlist we had an aptitute round.
Tips: Answer according to your own judgement. Dont try to be too precise.

Round: HR Interview
Experience: I said they think I am a workaholic as I prefer to complete my work before chilling with them.

College Name: NIT Durgapur

Interview Preparation Tips

Round: HR Interview
Experience: Interview at 11 pm. Stressed environment, close to stress interview.
SELECTION PROCEDURE:
1.Online Test
2. GD
3. PI(HR)
GD TOPICS :
Topic 1 : How can education system benefit from interdisciplinary methods.
Topic 2 : Interconnected problems in the field of movie making.
INTERVIEW EXPERIENCE:
So you can speak German? Describe MS Dhoni in german. They opened Google Translate to counter check the words they wanted to be translated in both Deutsch and Spanish. Your profile speaks of an inclination towards software skills, why do you want to join an analytics company? Justify your action in two reasons as to why are you sitting here interviewing for the post of a data scientist rather than apply for a software engineer when this CV speaks highly of computer science? What is Finite Element Method? Explain. How relevant is your work in Computer Vision? Breakdown the tagline of Audi and translate accordingly. What is "Technik für Mobel" ? What are your current projects? Answer : Microsoft Xbox Kinect, Gesture Recognition. Counter question : But at Musimga you'd be doing far simpler stuff.? Counter suggestion : Why don't you go for MS?


Tips: Keep your cool during counter questions. Prepare your profile and CV well. Rest all is your hard work and groomed personal talents and acquired skills you learnt over the internet.

Skills: Ability To Cope Up With Stress, Spanish, German, Finite Element Modeling - FEM, Foreign Language
College Name: NIT Raipur
Funny Moments: Another HR enters in the midst of my interview and asks with bewildered amazement : What language is he speaking?
The other HR, "German".

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed in Dec 2024. There were 2 interview rounds.

Round 1 - Technical 

(2 Questions)

  • Q1. On Project from resume
  • Q2. GenAI basics
Round 2 - Technical 

(2 Questions)

  • Q1. RAG, LLM, Azure OpenAI
  • Q2. Python questions

Interview Preparation Tips

Topics to prepare for Axtria Data Scientist interview:
  • genai
  • Python
  • Llm
Interview preparation tips for other job seekers - Good interview process, good interviewer

I applied via Recruitment Consultant and was interviewed in Dec 2018. There were 3 interview rounds.

Interview Questionnaire 

11 Questions

  • Q1. 1. Why Machine Learning?
  • Q2. 2. Why did you choose Data Science Field?
  • Ans. 

    I chose Data Science field because of its potential to solve complex problems and make a positive impact on society.

    • Fascination with data and its potential to drive insights

    • Desire to solve complex problems and make a positive impact on society

    • Opportunity to work with cutting-edge technology and tools

    • Ability to work in a variety of industries and domains

    • Examples: Predictive maintenance in manufacturing, fraud detection

  • Answered by AI
  • Q3. 3. What about Linear Regression? (Theory Part)
  • Q4. 4. What is the difference between Linear Regression and Logistic Regression?
  • Ans. 

    Linear Regression is used for predicting continuous numerical values, while Logistic Regression is used for predicting binary categorical values.

    • Linear Regression predicts a continuous output, while Logistic Regression predicts a binary output.

    • Linear Regression uses a linear equation to model the relationship between the independent and dependent variables, while Logistic Regression uses a logistic function.

    • Linear Regr...

  • Answered by AI
  • Q5. 5. Explain Confusion Matrix?
  • Ans. 

    Confusion matrix is a table used to evaluate the performance of a classification model.

    • It is a 2x2 matrix that shows the number of true positives, false positives, true negatives, and false negatives.

    • It helps in calculating various metrics like accuracy, precision, recall, and F1 score.

    • It is useful in identifying the strengths and weaknesses of a model and improving its performance.

    • Example: In a binary classification p...

  • Answered by AI
  • Q6. 6. Can we use confusion matrix in Linear Regression?
  • Ans. 

    No, confusion matrix is not used in Linear Regression.

    • Confusion matrix is used to evaluate classification models.

    • Linear Regression is a regression model, not a classification model.

    • Evaluation metrics for Linear Regression include R-squared, Mean Squared Error, etc.

  • Answered by AI
  • Q7. 7. Explain KNN Algorithm?
  • Ans. 

    KNN is a non-parametric algorithm used for classification and regression tasks.

    • KNN stands for K-Nearest Neighbors.

    • It works by finding the K closest data points to a given test point.

    • The class or value of the test point is then determined by the majority class or average value of the K neighbors.

    • KNN can be used for both classification and regression tasks.

    • It is a simple and easy-to-understand algorithm, but can be compu

  • Answered by AI
  • Q8. 8. Explain Random Forest and Decision Tree?
  • Ans. 

    Random Forest is an ensemble learning method that builds multiple decision trees and combines their outputs to improve accuracy.

    • Random Forest is a type of supervised learning algorithm used for classification and regression tasks.

    • It creates multiple decision trees and combines their outputs to make a final prediction.

    • Each decision tree is built using a random subset of features and data points to reduce overfitting.

    • Ran...

  • Answered by AI
  • Q9. 9. One Tricky Mathematical Question !
  • Q10. 10. What are the Projects you have done?
  • Ans. 

    I have worked on various projects involving data analysis, machine learning, and predictive modeling.

    • Developed a predictive model to forecast customer churn for a telecommunications company.

    • Built a recommendation system using collaborative filtering for an e-commerce platform.

    • Performed sentiment analysis on social media data to understand customer opinions and preferences.

    • Implemented a fraud detection system using anom...

  • Answered by AI
  • Q11. I didn't get shortlisted for 2nd Round.

Interview Preparation Tips

General Tips: anyone who wants to go in data science field should actually be interested in the field not the money. They should be good in Statistics, Probability and Theory part of ML algorithms.
They will ask you about the projects you have mentioned in resume and all the questions will be from that part.
Skills: Communication, Body Language, Problem Solving, Analytical Skills
Duration: 1-4 weeks

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via LinkedIn and was interviewed in Feb 2023. There were 6 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 Resume tips
Round 2 - Coding Test 

Platform HackerEarth
9 Questions
2 Coding Questions on Python based on Dynamic Programming
7 Questions MCQ on Data Science and SQL

Round 3 - Technical 

(1 Question)

  • Q1. Data Science Projects discussion Python Coding by sharing screen
Round 4 - Technical 

(4 Questions)

  • Q1. Data Science Projects Detailed Questions
  • Q2. In Depth Knowledge on any one of your project.
  • Q3. Cross Questioning on Regression, Classfication Problems. Dummy Variable Trap Statistics Questions
  • Q4. Questions on Deep Learning Models working and architecture like RNN Exploding/Vanishing Gradient Problem, Solutions like LSTM, CNN model working and different terminologies used.
Round 5 - Technical 

(1 Question)

  • Q1. Again this round was pure Technical. All questions were on Data Science Projects and scenario based. 2 Questions on Probability and puzzle based.
Round 6 - HR 

(1 Question)

  • Q1. Final Round Discussion about Company's Policies and Roles. Your Expectations from the company, the kind of role you are looking for and why Tiger.

Interview Preparation Tips

Interview preparation tips for other job seekers - Just have knowledge of everything what you have mentioned in your resume, small small details, different terms used often in each model and remember to have working knowledge of each model's architecture.
Be confident with your responses.

I applied via Referral and was interviewed in Aug 2022. There were 3 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 Resume tips
Round 2 - HR 

(1 Question)

  • Q1. What are the relevant projects in Data science & expertise in whatt all tools & technologies
  • Ans. 

    Relevant projects in Data Science and expertise in tools and technologies

    • Projects: Predictive modeling, Natural Language Processing, Computer Vision, Recommender Systems, Time Series Analysis

    • Tools: Python, R, SQL, Tableau, Hadoop, Spark, TensorFlow, Keras, Scikit-learn

    • Technologies: Machine Learning, Deep Learning, Big Data, Cloud Computing, Data Visualization

  • Answered by AI
Round 3 - Technical 

(1 Question)

  • Q1. He asked only coding question in Python & time duration is less & expectations are pretty unclear .

Interview Preparation Tips

Topics to prepare for Tiger Analytics Data Scientist interview:
  • python
Interview preparation tips for other job seekers - Prepare Python properly & clearly check interviewer expectations

Skills evaluated in this interview

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
-

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

Round 1 - Technical 

(1 Question)

  • Q1. Dicision Tree algorithm
  • Ans. 

    Decision Tree algorithm is a supervised learning algorithm used for classification and regression tasks.

    • Decision Tree algorithm is based on a tree-like model of decisions and their possible consequences.

    • It uses a set of rules to split the data into branches and make predictions at the leaf nodes.

    • The algorithm selects the best attribute to split the data based on certain criteria like information gain or Gini index.

    • Deci...

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Naukri.com and was interviewed in May 2024. There were 4 interview rounds.

Round 1 - Coding Test 

Screening round,2 programming and 5 MCQs

Round 2 - Technical 

(1 Question)

  • Q1. Basic python coding questions
Round 3 - Technical 

(1 Question)

  • Q1. Based on CV , previous projects
Round 4 - HR 

(1 Question)

  • Q1. General HR discussion
Interview experience
5
Excellent
Difficulty level
Hard
Process Duration
Less than 2 weeks
Result
Not Selected

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

Round 1 - Coding Test 

This round Medium level leet code question

Round 2 - Case Study 

Cpg case study logistic regression linear regression

Round 3 - HR 

(1 Question)

  • Q1. Job switch reason past project experience
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Gramener Interview FAQs

How many rounds are there in Gramener Data Science Engineer interview?
Gramener interview process usually has 4 rounds. The most common rounds in the Gramener interview process are Technical, Resume Shortlist and Coding Test.
How to prepare for Gramener Data Science Engineer interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Gramener. The most common topics and skills that interviewers at Gramener expect are Data Management, Data Science, Data Visualization, Python and RDBMS.
What are the top questions asked in Gramener Data Science Engineer interview?

Some of the top questions asked at the Gramener Data Science Engineer interview -

  1. question on python, data structu...read more
  2. questions on oops conce...read more

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Gramener Data Science Engineer Interview Process

based on 1 interview

Interview experience

4
  
Good
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Gramener Data Science Engineer Salary
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₹5 L/yr - ₹15 L/yr
8% less than the average Data Science Engineer Salary in India
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based on 4 reviews

3.7/5

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3.4

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3.7

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3.4

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