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Dabur Research Foundation Research Scientist 1 Interview Questions and Answers
Dabur Research Foundation Research Scientist 1 Interview Experiences
1 interview found
RACHNA KAUSHIK
(4 Questions)
- Q1. Which dye is used in staining
- Q2. What is cell culture
- Q3. What are my hobbies
- Ans.
My hobbies include hiking, reading, and playing the piano.
Hiking: I enjoy exploring nature trails and challenging myself with different terrains.
Reading: I love getting lost in a good book, especially fiction and mystery genres.
Playing the piano: I find relaxation and joy in creating music and improving my skills.
- Q4. What is difference in plant cell culture and animals cell 6
- Ans.
Plant cell culture involves growing plant cells in a controlled environment, while animal cell culture involves growing animal cells.
Plant cell culture is typically done in a solid or liquid medium containing nutrients and growth hormones.
Animal cell culture is often done in a similar medium, but may require additional factors such as specific growth factors or hormones.
Plant cells have a rigid cell wall, while animal ...
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Lakshman Bhavana
Selected
I applied via campus placement at Sastra University and was interviewed in Sep 2024. There were 2 interview rounds.
Along with coding round..there's a communication test at the end
(2 Questions)
- Q1. There's ntg to ask about technical for me..
- Q2. Behavioural questions
Selected
I applied via Referral and was interviewed in May 2024. There were 3 interview rounds.
I was asked to write SQL queries for 3rd highest salary of the employee, some name filtering, group by tasks.
Python code to find the index of the maximum number without using numpy.
(1 Question)
- Q1. Explain the Project undertaken during the research and follow-up questions
(1 Question)
- Q1. Write pandas query to separate the names as first and last name from the full name. Drop the duplicate columns and also the missing values. Write output for the Python code. Write SQL query to retrieve t...
- Ans.
Answering questions related to data science concepts and techniques.
Recall is the ratio of correctly predicted positive observations to the total actual positives. Precision is the ratio of correctly predicted positive observations to the total predicted positives.
To reduce variance in an ensemble model, techniques like bagging, boosting, and stacking can be used. Bagging involves training multiple models on different ...
Interview Preparation Tips
- Python
- Pandas
- SQL
- Machine Learning
Skills evaluated in this interview
Data Scientist Interview Questions & Answers
Acuity Knowledge Partners
Anonymous
posted on 11 Sep 2024
I applied via Company Website and was interviewed in Aug 2024. There was 1 interview round.
(2 Questions)
- Q1. Explain the RAG pipeline?
- Ans.
RAG pipeline is a data processing pipeline used in data science to categorize data into Red, Amber, and Green based on certain criteria.
RAG stands for Red, Amber, Green which are used to categorize data based on certain criteria
Red category typically represents data that needs immediate attention or action
Amber category represents data that requires monitoring or further investigation
Green category represents data that...
- Q2. Explain Confusion metrics
- Ans.
Confusion metrics are used to evaluate the performance of a classification model by comparing predicted values with actual values.
Confusion matrix is a table that describes the performance of a classification model.
It consists of four different metrics: True Positive, True Negative, False Positive, and False Negative.
These metrics are used to calculate other evaluation metrics like accuracy, precision, recall, and F1 s...
Skills evaluated in this interview
I applied via Company Website and was interviewed in Jun 2024. There were 2 interview rounds.
Basic aptitude , tech aptitude
(2 Questions)
- Q1. What is overfitting
- Q2. How to handle missing values
DSA and ML, AI, Coding question
(1 Question)
- Q1. Case study which was easy
(1 Question)
- Q1. In depth questions on ML
Given 6 coding qns related to java and html and also ML.
(1 Question)
- Q1. Explain abt projects and qns related to ML.
- Ans.
Projects in machine learning involve developing algorithms to analyze and interpret data for various applications.
Developing a recommendation system for an e-commerce website
Predicting customer churn for a telecommunications company
Classifying images in a computer vision project
Anomaly detection in network traffic for cybersecurity
Natural language processing for sentiment analysis
(1 Question)
- Q1. Basic hr qns why straive?
Skills evaluated in this interview
Selected
I applied via Approached by Company and was interviewed before Mar 2023. There was 1 interview round.
(2 Questions)
- Q1. Past projects of machine learning
- Ans.
Developed a predictive model for customer churn using machine learning algorithms.
Used Python and scikit-learn library for data preprocessing and model building
Performed feature engineering to improve model performance
Evaluated model performance using metrics like accuracy, precision, and recall
- Q2. Distributed computing and spark questions
Skills evaluated in this interview
I applied via campus placement at Government College Of Education, Chandigarh, Chandigarh and was interviewed in Aug 2024. There were 2 interview rounds.
Aptitude test consists of 40 questions.
(2 Questions)
- Q1. Introduce yourself with ur projects
- Ans.
I am a data scientist with experience in developing predictive models and analyzing large datasets.
Developed a predictive model for customer churn prediction using machine learning algorithms
Analyzed sales data to identify key trends and patterns for business optimization
Implemented natural language processing techniques for sentiment analysis of customer reviews
- Q2. Problem statement of a case that needs solutions.
- Ans.
Develop a predictive model to identify potential customers for a new product launch.
Define the target variable and features to be used in the model
Collect and preprocess relevant data for training the model
Select an appropriate machine learning algorithm and train the model
Evaluate the model's performance using metrics like accuracy, precision, and recall
Use the model to predict potential customers for the new product
Selected
I applied via Naukri.com and was interviewed in Oct 2023. There were 4 interview rounds.
Sql, python, Statistics mcq, Aptitude test. These were medium level questions.
(3 Questions)
- Q1. SQL and python, time complexity
- Q2. Make 2 lists a=[1,2,3,4] b=[9,8,5,5,2,3,3,4,1,1,10,9,2,3,4,10,10,9,7,7,8] Write a program to remove duplicate of b and keep only those elements of b which are not present in a, and the final list should ...
- Ans.
Remove duplicates from list b, keep elements not in list a, and sort in ascending order.
Create a set from list b to remove duplicates
Use list comprehension to keep elements not in list a
Sort the final list in ascending order
- Q3. SQL question Remove duplicate from a table tab1
- Ans.
Use the DISTINCT keyword in SQL to remove duplicates from a table.
Use the SELECT DISTINCT statement to retrieve unique rows from the table.
Identify the columns that should be used to determine uniqueness.
Example: SELECT DISTINCT column1, column2 FROM tab1;
Given 2 case studies on data science and asked different possibilities to improve the models.
How to work with imbalance dataset.
How to remove null values, what is features engineering.
What is PCA
What is the working of XGBOOST
(1 Question)
- Q1. What was last project, tell me in detail. There were different technical questions related to my project
Interview Preparation Tips
All the metrics of evaluating a model.
Linear regression, logestic regression, random forest, decission tree, adaboost, Gradient boosting, XGb in detail.
Recall, precision roc_curve. Auc, f1 score, mse,mae, r2, adjusted r2 score.
Is it possible that r2 score appears in minus
Skills evaluated in this interview
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Dabur Research Foundation Research Scientist 1 Reviews and Ratings
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Rating in categories
|
Research Scientist
36
salaries
|  ₹2.2 L/yr - ₹7.3 L/yr |
|
Senior Research Scientist
33
salaries
| ₹5 L/yr - ₹10 L/yr |
|
Research Scientist II
15
salaries
| ₹3.8 L/yr - ₹5.3 L/yr |
|
Research Trainee
14
salaries
| ₹2.7 L/yr - ₹3.3 L/yr |
|
Research Associate
13
salaries
| ₹1.8 L/yr - ₹4.6 L/yr |
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