Boeing Senior Data Science Consultant Interview Questions and Answers for Experienced

Medium to hard level questions were asked and that mostly covers basics of DSA

Q1. Oops ,DBMS and DSA logical questions
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Q1. What is gcd? And explain it
Ans. 
gcd stands for greatest common divisor, the largest positive integer that divides two or more numbers without leaving a remainder.
• gcd is used to find the largest integer that can evenly divide two or more numbers.

• It is commonly used in mathematics and computer science algorithms.

• For example, the gcd of 12 and 18 is 6, as 6 is the largest number that can divide both 12 and 18 without leaving a remainder.
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Q2. What is arc and explain it
Ans. 
ARC stands for Automatic Reference Counting, a memory management technique used in programming languages like Objective-C and Swift.
• ARC automatically tracks and manages the memory used by objects in a program

• It increases the retain count of an object when it is referenced and decreases it when it is no longer needed

• ARC helps prevent memory leaks and retain cycles in iOS and macOS development
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About previous experiences

Q1. Salary and job profile
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Q1. Basics of linear regression
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Q1. Machine learning in depth
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Tree algorithm about some riddels

Based on different scenarios they interviewed me

Q1. How comfortable I am moving to qatar
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Q2. Salary expectstion
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Hackerrank test basic kotlin and android

Q1. Picks one of the Projects to discuss the structure and methodology.
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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
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Q3. Basic ML Questions about Resume Projects
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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...read more
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Q5. Basics about Forescasting.
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