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Boeing Data Scientist Interview Questions and Answers
Boeing Data Scientist Interview Experiences
1 interview found
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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Anonymous
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
I applied via Recruitment Consulltant and was interviewed in Aug 2024. There were 2 interview rounds.
(2 Questions)
- Q1. Explain how did you handle the imbalance in data
- Ans.
I handled data imbalance by using techniques like oversampling, undersampling, SMOTE, or using ensemble methods.
Used oversampling to increase minority class instances
Used undersampling to decrease majority class instances
Applied SMOTE (Synthetic Minority Over-sampling Technique) to generate synthetic samples for minority class
Utilized ensemble methods like Random Forest or Gradient Boosting to handle imbalance
- Q2. Write a sql query for the given problem statement. Can be solved using advanced concepts like lead and lag
Advanced sql and basics of data science
Interview Preparation Tips
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
Selected
I applied via Referral and was interviewed in Jan 2023. There were 2 interview rounds.
(2 Questions)
- Q1. Asked about Projects ?
- Q2. Asked about algorithms
Interview Preparation Tips
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
I applied via Recruitment Consulltant and was interviewed in Aug 2024. There were 2 interview rounds.
(2 Questions)
- Q1. Explain how did you handle the imbalance in data
- Ans.
I handled data imbalance by using techniques like oversampling, undersampling, SMOTE, or using ensemble methods.
Used oversampling to increase minority class instances
Used undersampling to decrease majority class instances
Applied SMOTE (Synthetic Minority Over-sampling Technique) to generate synthetic samples for minority class
Utilized ensemble methods like Random Forest or Gradient Boosting to handle imbalance
- Q2. Write a sql query for the given problem statement. Can be solved using advanced concepts like lead and lag
Advanced sql and basics of data science
Interview Preparation Tips
I applied via Naukri.com and was interviewed in Feb 2024. There was 1 interview round.
(5 Questions)
- Q1. Picks one of the Projects to discuss the structure and methodology.
- Q2. Reverse a String
- Ans.
Reverse a given string
Use built-in functions like reverse() or slice() in Python
Iterate through the string in reverse order and append characters to a new string
Convert the string to an array of characters, reverse the array, and join it back into a string
- Q3. Basic ML Questions about Resume Projects
- Q4. What is Regularization?
- Ans.
Regularization is a technique used to prevent overfitting in machine learning models by adding a penalty term to the loss function.
Regularization helps to reduce the complexity of the model by penalizing large coefficients.
It adds a penalty term to the loss function, such as L1 (Lasso) or L2 (Ridge) regularization.
Regularization helps to improve the generalization of the model by discouraging overfitting.
Examples of re...
- Q5. Basics about Forescasting.
Skills evaluated in this interview
I applied via Recruitment Consulltant and was interviewed in Feb 2024. There were 3 interview rounds.
Hackerank Assignment
(1 Question)
- Q1. Coding and ML questions
(1 Question)
- Q1. About projects and questions related to that
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