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I applied via Naukri.com and was interviewed in Dec 2024. There was 1 interview round.
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.
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 ...
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.
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
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
I applied via Referral and was interviewed in Mar 2024. There were 4 interview rounds.
Test consisted 7 sections which lasted for more than a hour. There were questions related to coding , sql , analytical questions etc.
1 python coding questions and 2 Sql question
2 case study question
Nielsen interview questions for designations
Top trending discussions
I was interviewed in Jan 2025.
I have 5 years of experience in analyzing large datasets to extract valuable insights and make data-driven decisions.
Analyzed customer behavior data to optimize marketing strategies
Built predictive models to forecast sales trends
Utilized machine learning algorithms to improve product recommendations
Presented findings to stakeholders in a clear and actionable manner
Questions related to work experience in data science field.
Asked about previous projects worked on
Inquired about specific data analysis techniques used
Discussed challenges faced and how they were overcome
posted on 11 Sep 2024
I applied via Company Website and was interviewed in Aug 2024. There was 1 interview round.
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...
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...
DSA and ML, AI, Coding question
I applied via Naukri.com and was interviewed in Feb 2024. There was 1 interview round.
Handling imbalanced datasets involves techniques like resampling, using different algorithms, and adjusting class weights.
Use resampling techniques like oversampling the minority class or undersampling the majority class.
Utilize algorithms that are robust to imbalanced datasets, such as Random Forest, XGBoost, or SVM.
Adjust class weights in the model to give more importance to the minority class.
Use techniques like SMO...
Basic aptitude question from rs aggarwal book.
Basic questions on python loops
Try to put foeth yiur point as there will 13 people in a panel
Given 6 coding qns related to java and html and also ML.
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
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