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Gramener Data Science Engineer Interview Questions and Answers
Gramener Data Science Engineer Interview Experiences
1 interview found
Anonymous
Selected
I applied via Campus Placement and was interviewed before Sep 2022. There were 4 interview rounds.
Test based on js, python, html and css
(1 Question)
- Q1. Questions on oops concepts
(1 Question)
- Q1. Question on python, data structures
Interview Preparation Tips
- python
- Javascript
Top trending discussions
Interview questions from similar companies
Sayantan Ghosh
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
Interview Preparation Tips
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
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".
Selected
I applied via Naukri.com and was interviewed in Dec 2024. There were 2 interview rounds.
(2 Questions)
- Q1. On Project from resume
- Q2. GenAI basics
(2 Questions)
- Q1. RAG, LLM, Azure OpenAI
- Q2. Python questions
Interview Preparation Tips
- genai
- Python
- Llm
rustam garg
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
- 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...
- 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...
- 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.
- 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
- 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...
- 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...
- Q11. I didn't get shortlisted for 2nd Round.
Interview Preparation Tips
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
Selected
I applied via LinkedIn and was interviewed in Feb 2023. There were 6 interview rounds.
Platform HackerEarth
9 Questions
2 Coding Questions on Python based on Dynamic Programming
7 Questions MCQ on Data Science and SQL
(1 Question)
- Q1. Data Science Projects discussion Python Coding by sharing screen
(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.
(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.
(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
Be confident with your responses.
I applied via Referral and was interviewed in Aug 2022. There were 3 interview rounds.
(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
(1 Question)
- Q1. He asked only coding question in Python & time duration is less & expectations are pretty unclear .
Interview Preparation Tips
- python
Skills evaluated in this interview
I applied via AmbitionBox and was interviewed in Jul 2023. There was 1 interview round.
(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...
Skills evaluated in this interview
Selected
I applied via Naukri.com and was interviewed in May 2024. There were 4 interview rounds.
Screening round,2 programming and 5 MCQs
(1 Question)
- Q1. Basic python coding questions
(1 Question)
- Q1. Based on CV , previous projects
(1 Question)
- Q1. General HR discussion
I applied via Company Website and was interviewed in Apr 2024. There were 3 interview rounds.
This round Medium level leet code question
Cpg case study logistic regression linear regression
(1 Question)
- Q1. Job switch reason past project experience
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