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Pratt & Whitney Data Scientist Interview Questions and Answers
Pratt & Whitney Data Scientist Interview Experiences
1 interview found
Selected
I applied via Approached by Company and was interviewed in Sep 2024. There were 3 interview rounds.
Based upon the profile vary, time series related problems, power BI
(2 Questions)
- Q1. Deep profile discussion
- Q2. Futuristic opinion analysis
(2 Questions)
- Q1. Salary discussion
- Q2. Basic questions
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I applied via campus placement at Birla Institute of Technology and Science (BITS), Pilani and was interviewed in Dec 2024. There were 2 interview rounds.
(1 Question)
- Q1. Basics of linear regression
(1 Question)
- Q1. Machine learning in depth
Data Scientist Interview Questions & Answers
Larsen & Toubro Limited
Anonymous
posted on 31 Jul 2024
I applied via Job Portal and was interviewed in Jul 2024. There were 2 interview rounds.
Python programming for 45 for minutes
(2 Questions)
- Q1. What are the hyperparameters of SVM
- Ans.
Hyperparameters of SVM include C, kernel, gamma, degree, and coef0.
C: Regularization parameter that controls the trade-off between achieving a low error on the training data and minimizing model complexity.
Kernel: Specifies the type of hyperplane used to separate the data.
Gamma: Kernel coefficient for 'rbf', 'poly', and 'sigmoid' kernels.
Degree: Degree of the polynomial kernel function.
Coef0: Independent term in kernel...
- Q2. How to tune that hyperparameters
- Ans.
Hyperparameters can be tuned using techniques like grid search, random search, and Bayesian optimization.
Grid search: Exhaustively search through a specified subset of hyperparameters.
Random search: Randomly sample hyperparameter combinations.
Bayesian optimization: Use probabilistic models to predict the performance of different hyperparameter configurations.
Skills evaluated in this interview
I applied via Walk-in and was interviewed in Mar 2024. There were 2 interview rounds.
Basic coding questions
(3 Questions)
- Q1. Explain in detail about current project? Reason for choosing the algorithm, evaluation metrics and analysis of data
- Ans.
Developed a predictive model for customer churn using logistic regression
Chose logistic regression for its interpretability and ability to handle binary outcomes
Evaluated model performance using accuracy, precision, recall, and F1 score
Analyzed customer data including demographics, purchase history, and customer service interactions
- Q2. Python and sql coding questions - basic
- Q3. Linear regression, xgboost, precision, recall, F1 Score,Correlation
(1 Question)
- Q1. What's your strength
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questions about working experiences and case study in english and french
Ashish Kumar Ray
I applied via Approached by Company and was interviewed in Mar 2022. There were 3 interview rounds.
(1 Question)
- Q1. What kind of project you have done give some brief. How you will avoid over fiting to model. How will you handle missing data points in a data frame. Why you want to join our company.
(1 Question)
- Q1. Behavioral question was asked by manager.
(1 Question)
- Q1. CTC discussion was done
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I applied via campus placement at Dr. B.R. Ambedkar National Institute of Technology (NIT), Jalandhar and was interviewed in Dec 2024. There was 1 interview round.
(2 Questions)
- Q1. Full form of CSS, time complexity of varies algorithm like mege sort, binary search
- Q2. Time complexity of varies algorithm like merge sort, binary search
Selected
I was interviewed before Nov 2023.
Based on different scenarios they interviewed me
(2 Questions)
- Q1. How comfortable I am moving to qatar
- Q2. Salary expectstion
I applied via campus placement at Birla Institute of Technology and Science (BITS), Pilani and was interviewed in Dec 2024. There were 2 interview rounds.
(1 Question)
- Q1. Basics of linear regression
(1 Question)
- Q1. Machine learning in depth
Data Scientist Interview Questions & Answers
Larsen & Toubro Limited
Anonymous
posted on 31 Jul 2024
I applied via Job Portal and was interviewed in Jul 2024. There were 2 interview rounds.
Python programming for 45 for minutes
(2 Questions)
- Q1. What are the hyperparameters of SVM
- Ans.
Hyperparameters of SVM include C, kernel, gamma, degree, and coef0.
C: Regularization parameter that controls the trade-off between achieving a low error on the training data and minimizing model complexity.
Kernel: Specifies the type of hyperplane used to separate the data.
Gamma: Kernel coefficient for 'rbf', 'poly', and 'sigmoid' kernels.
Degree: Degree of the polynomial kernel function.
Coef0: Independent term in kernel...
- Q2. How to tune that hyperparameters
- Ans.
Hyperparameters can be tuned using techniques like grid search, random search, and Bayesian optimization.
Grid search: Exhaustively search through a specified subset of hyperparameters.
Random search: Randomly sample hyperparameter combinations.
Bayesian optimization: Use probabilistic models to predict the performance of different hyperparameter configurations.
Skills evaluated in this interview
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