AmbitionBox
Interview Questions
- Reviews
- Salaries
- Interview Questions
- About Company
- Benefits
- Jobs
- Office Photos
- Community
Add office photos
Filter interviews by
Gramener Lead Data Consultant Interview Questions and Answers
Gramener Lead Data Consultant Interview Experiences
1 interview found
Anonymous
Interview Questionnaire
1 Question
- Q1. Work Ex, Data visualization, Data stories
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".
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
I was interviewed before Feb 2024.
(1 Question)
- Q1. Project related questions, from CV
(1 Question)
- Q1. On deep learning, from cv
(1 Question)
- Q1. Basic HR questions like why you want to change, etc
Selected
I applied via Company Website and was interviewed before Oct 2023. There was 1 interview round.
ML questions alogorithims
Interview Preparation Tips
I applied via Campus Placement and was interviewed in Feb 2024. There were 2 interview rounds.
Coding test which requires python and few aptitude and technical questions
(1 Question)
- Q1. Python questions and questions based on resume
K K Aryaa
(2 Questions)
- Q1. It was about machine learning
- Q2. It was about Genai RAG
I applied via Naukri.com and was interviewed in Aug 2024. There were 2 interview rounds.
(2 Questions)
- Q1. How to handle missing values
- Ans.
Handle missing values by imputation, deletion, or using algorithms that can handle missing data.
Impute missing values using mean, median, mode, or predictive modeling
Delete rows or columns with missing values if they are insignificant
Use algorithms like XGBoost, Random Forest, or LightGBM that can handle missing data
- Q2. Linear equations model metrics
(2 Questions)
- Q1. Precession vs recall?
- Ans.
Precision measures the accuracy of positive predictions, while recall measures the ability to find all positive instances.
Precision is the ratio of correctly predicted positive observations to the total predicted positives.
Recall is the ratio of correctly predicted positive observations to all actual positives.
Precision is important when the cost of false positives is high, while recall is important when the cost of fa...
- Q2. Clustering evaluation metrics
Skills evaluated in this interview
Krishna Anand
I applied via Campus Placement
Aptitude + Technical Questions
Coding Questions of SQL and DSA
(4 Questions)
- Q1. Transpose a matrix in python and machine learning questions
- Ans.
To transpose a matrix in Python, use numpy.transpose() or the T attribute.
Use numpy.transpose() function to transpose a matrix.
Alternatively, use the T attribute of a numpy array.
Example: np.transpose(matrix) or matrix.T
- Q2. What are numpy and pandas
- Ans.
NumPy is a library for numerical computing in Python, while Pandas is a data manipulation and analysis tool.
NumPy provides support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.
Pandas offers data structures like DataFrame for easy data manipulation and analysis, with tools for reading and writing data from various file formats.
Both librari...
- Q3. Visualization libraries in python
- Ans.
Python has various visualization libraries like Matplotlib, Seaborn, Plotly, and Bokeh.
Matplotlib is a widely used library for creating static, interactive, and animated plots.
Seaborn is built on top of Matplotlib and provides a high-level interface for creating attractive and informative statistical graphics.
Plotly is great for creating interactive plots and dashboards.
Bokeh is another interactive visualization librar...
- Q4. Object Oriented Programing
Interview Preparation Tips
Skills evaluated in this interview
Gramener Interview FAQs
Tell us how to improve this page.
Gramener Interviews By Designations
- Gramener Data Scientist Interview Questions
- Gramener Software Testing Interview Questions
- Gramener Azure Data Engineer Interview Questions
- Gramener Senior Data Analyst Interview Questions
- Gramener Senior Android Developer Interview Questions
- Gramener Translation Associate Interview Questions
- Gramener Data Science Engineer Interview Questions
- Gramener Lead Data Consultant Interview Questions
- Show more
Interview Questions for Popular Designations
- Data Analyst Interview Questions
- Data Engineer Interview Questions
- Data Scientist Interview Questions
- Data Entry Operator Interview Questions
- Senior Data Engineer Interview Questions
- Senior Data Analyst Interview Questions
- Senior Data Scientist Interview Questions
- Lead Data Engineer Interview Questions
- Show more
Interview Questions from Similar Companies
Fast track your campus placements
Gramener Lead Data Consultant Reviews and Ratings
based on 2 reviews
Rating in categories
|
Senior Data Science Engineer
44
salaries
|  ₹0 L/yr - ₹0 L/yr |
|
Data Scientist
41
salaries
| ₹0 L/yr - ₹0 L/yr |
|
Data Science Engineer
31
salaries
| ₹0 L/yr - ₹0 L/yr |
|
Senior Data Scientist
22
salaries
| ₹0 L/yr - ₹0 L/yr |
|
Lead Data Consultant
16
salaries
| ₹0 L/yr - ₹0 L/yr |
Fractal Analytics
Mu Sigma
Tiger Analytics
LatentView Analytics
- Home >
- Interviews >
- Gramener Interview Questions >
- Gramener Lead Data Consultant Interview Questions
