Filter interviews by
Easy with python questions
I applied via Naukri.com and was interviewed before May 2023. There was 1 interview round.
I have implemented customer analytics in various industries including e-commerce and retail.
Implemented customer segmentation analysis to identify different customer groups based on behavior and preferences
Utilized predictive modeling techniques to forecast customer lifetime value and likelihood of churn
Developed recommendation systems to personalize product offerings and improve customer engagement
Used A/B testing to ...
I have experience deploying solutions on AWS, Azure, and Google Cloud Platform.
AWS (Amazon Web Services)
Azure
Google Cloud Platform
posted on 5 Feb 2022
I applied via Referral and was interviewed before Feb 2021. There were 3 interview rounds.
Sql and basis python
Business related case study
posted on 23 Apr 2022
The coding round was relatively easy. A sufficient amount of preparation on LeetCode should be beneficial, along with reviewing the sample questions.
posted on 13 May 2024
I applied via Naukri.com and was interviewed before May 2023. There were 4 interview rounds.
2 sections. First, multiple choice questions regarding Ml algo, SQl. Second, ML coding problem.
posted on 5 Feb 2024
I applied via Referral and was interviewed in Jan 2024. There were 3 interview rounds.
I applied via Approached by Company and was interviewed in Feb 2023. There were 4 interview rounds.
Basic coding questions related to data science
Imbalanced data in text analytics can be handled by techniques like oversampling, undersampling, and SMOTE.
Use oversampling to increase the number of instances in the minority class
Use undersampling to decrease the number of instances in the majority class
Use SMOTE to generate synthetic samples for the minority class
Use cost-sensitive learning algorithms to assign higher misclassification costs to the minority class
Use...
I applied via Approached by Company and was interviewed in Jan 2024. There was 1 interview round.
The test consisted 1 programming question, 2 SQL questions, 2 Python questions, and 10 ML questions. The difficulty level was from easy to medium range. However, the platform was very slow and it was a timed test. They should either conduct the test in a friendly platform or increase the time allotted for each section.
I applied via Approached by Company and was interviewed before Sep 2022. There were 3 interview rounds.
Ridge and Lasso regression are both regularization techniques used in linear regression to prevent overfitting.
Ridge regression adds a penalty equivalent to the square of the magnitude of coefficients, while Lasso regression adds a penalty equivalent to the absolute value of the magnitude of coefficients.
Ridge regression shrinks the coefficients towards zero but never exactly to zero, while Lasso regression can shrink ...
Boosting focuses on improving the performance of weak learners sequentially, while bagging uses parallel ensemble learning with bootstrapping.
Boosting combines multiple weak learners to create a strong learner by giving more weight to misclassified instances in each iteration.
Bagging creates multiple subsets of the training data through bootstrapping and trains each subset independently to reduce variance.
Examples: Ada...
I applied via Naukri.com and was interviewed in Aug 2024. There were 3 interview rounds.
Python Coding Questions with
Bubble sort example Question using python
Previous projects based questions
based on 1 interview
Interview experience
based on 7 reviews
Rating in categories
Senior Applied Data Scientist
129
salaries
| ₹0 L/yr - ₹0 L/yr |
Lead Applied Data Scientist
86
salaries
| ₹0 L/yr - ₹0 L/yr |
Applied Data Scientist
81
salaries
| ₹0 L/yr - ₹0 L/yr |
Senior Engineer
68
salaries
| ₹0 L/yr - ₹0 L/yr |
Senior Data Scientist
50
salaries
| ₹0 L/yr - ₹0 L/yr |
Fractal Analytics
Mu Sigma
AbsolutData
Algonomy