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ThoughtWorks Data Scientist Interview Questions and Answers
ThoughtWorks Data Scientist Interview Experiences
1 interview found
Astha Agarwal
Selected
I applied via campus placement at Dehradun Institute of Technology, Dehradun and was interviewed before Oct 2023. There were 3 interview rounds.
The first was a mcq based coding round for campus placement
This was a pairing coding round
(1 Question)
- Q1. Explain different unsupervised algo
- Ans.
Unsupervised algorithms are used to find patterns in data without labeled outcomes.
K-means clustering: partitions data into K clusters based on similarity
Hierarchical clustering: creates a tree of clusters based on similarity
Principal Component Analysis (PCA): reduces dimensionality by finding orthogonal components
Association rule mining: discovers interesting relationships between variables in large datasets
Skills evaluated in this interview
Interview questions from similar companies
(2 Questions)
- Q1. Write a few python queries and some live sql coding and pyspark coding
- Q2. Machine learning questions. Way too deep. which is not even required
Interview Preparation Tips
I applied via Naukri.com and was interviewed in May 2024. There were 2 interview rounds.
(1 Question)
- Q1. How to treat multicollinearity, imbalanced dataset
- Ans.
Multicollinearity can be treated by using techniques like feature selection, PCA, or regularization. Imbalanced datasets can be addressed by resampling techniques like oversampling or undersampling.
For multicollinearity, consider using techniques like feature selection to remove redundant variables, PCA to reduce dimensionality, or regularization like Lasso or Ridge regression.
For imbalanced datasets, try resampling te...
(2 Questions)
- Q1. Logistic regression in detail
- Ans.
Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.
Logistic regression is used when the dependent variable is binary (0/1, True/False, Yes/No, etc.)
It estimates the probability that a given observation belongs to a particular category.
The output of logistic regression is a probability score between 0 and 1.
It uses the logistic function...
- Q2. Project related questions based on Machine learning
Interview Preparation Tips
Skills evaluated in this interview
I applied via Naukri.com and was interviewed in Sep 2023. There were 4 interview rounds.
(1 Question)
- Q1. Data science related areas
Case study related to semantic search
(1 Question)
- Q1. Questions based on case study
I applied via Company Website and was interviewed in Aug 2023. There were 4 interview rounds.
(1 Question)
- Q1. Concepts and tools
Coding on the tools we use
(1 Question)
- Q1. Not cleared the round
Interview Preparation Tips
(2 Questions)
- Q1. Write a few python queries and some live sql coding and pyspark coding
- Q2. Machine learning questions. Way too deep. which is not even required
Interview Preparation Tips
I applied via Naukri.com and was interviewed in May 2024. There were 2 interview rounds.
(1 Question)
- Q1. How to treat multicollinearity, imbalanced dataset
- Ans.
Multicollinearity can be treated by using techniques like feature selection, PCA, or regularization. Imbalanced datasets can be addressed by resampling techniques like oversampling or undersampling.
For multicollinearity, consider using techniques like feature selection to remove redundant variables, PCA to reduce dimensionality, or regularization like Lasso or Ridge regression.
For imbalanced datasets, try resampling te...
(2 Questions)
- Q1. Logistic regression in detail
- Ans.
Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.
Logistic regression is used when the dependent variable is binary (0/1, True/False, Yes/No, etc.)
It estimates the probability that a given observation belongs to a particular category.
The output of logistic regression is a probability score between 0 and 1.
It uses the logistic function...
- Q2. Project related questions based on Machine learning
Interview Preparation Tips
Skills evaluated in this interview
I applied via Naukri.com and was interviewed in Sep 2023. There were 4 interview rounds.
(1 Question)
- Q1. Data science related areas
Case study related to semantic search
(1 Question)
- Q1. Questions based on case study
I applied via Company Website and was interviewed in Aug 2023. There were 4 interview rounds.
(1 Question)
- Q1. Concepts and tools
Coding on the tools we use
(1 Question)
- Q1. Not cleared the round
Interview Preparation Tips
Associate Data Scientist Interview Questions & Answers
Wipro Digital
Anonymous
posted on 11 Oct 2020
Interview Questionnaire
1 Question
- Q1. How to check given two random variables are independent. Why it is important for Naive Bayes classification.
- Ans.
To check if two random variables are independent and its importance in Naive Bayes classification.
Check if the joint probability of the two variables is equal to the product of their marginal probabilities.
If the joint probability is not equal to the product of the marginal probabilities, then the variables are dependent.
Independence assumption is important in Naive Bayes classification as it simplifies the calculation...
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