Applied Materials Data Scientist Interview Questions and Answers

Q1. Dropout in. Deep learning
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Q1. What is Adaboost?
Ans. 
Adaboost is a machine learning algorithm that combines multiple weak learners to create a strong learner.
• Adaboost stands for Adaptive Boosting.

• It works by adjusting the weights of incorrectly classified instances so that subsequent weak learners focus more on them.

• The final prediction is made by combining the predictions of all the weak learners, weighted by their accuracy.

• Example: Adaboost is commonly used in face det
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Q2. Print the binary tree in different order
Ans. 
Printing a binary tree in different orders
• Use inorder traversal to print the binary tree in ascending order

• Use preorder traversal to print the binary tree in root-left-right order

• Use postorder traversal to print the binary tree in left-right-root order
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Few standard dsa questions were asked.

Q1. Explain projects
Ans. 
Projects are specific tasks or assignments that require a set of skills and resources to achieve a particular goal or outcome.
• Projects involve defining objectives and deliverables

• They require planning, execution, and monitoring

• Projects often have timelines and budgets

• Examples: Data analysis project to identify customer trends, Project to implement a new software system
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Q2. Introduce urself
Ans. 
I am a data analyst with a strong background in statistics and data visualization.
• I have a Bachelor's degree in Statistics from XYZ University.

• I have 3 years of experience working as a data analyst at ABC Company.

• Proficient in using tools like Excel, SQL, and Tableau for data analysis.

• I have experience in creating reports and dashboards to present data insights to stakeholders.
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Q1. The Interviewer displayed a block of Deep Learning code and asked me to explain it
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Q1. Tell me about yourself
Ans. 
I am a data scientist with a background in statistics and machine learning, passionate about solving complex problems using data-driven approaches.
• Background in statistics and machine learning

• Experience in analyzing large datasets

• Skilled in programming languages like Python and R

• Strong problem-solving skills

• Passionate about leveraging data to drive insights and decision-making
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Q2. Why consulting?
Ans. 
Consulting allows me to work on a variety of projects, industries, and challenges, providing valuable experience and exposure.
• Opportunity to work on diverse projects and industries

• Exposure to different challenges and problem-solving scenarios

• Ability to apply expertise in various contexts

• Opportunity to collaborate with different teams and clients
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Test was conducted on skills like Advanced excel, MySQL, Analytical skills and understanding of business domain. The test was time bound and with camera on.

Q1. They questions on projects done by me and my past relevant experience. Also, they asked technical questions regarding Python, MySQL, Tableau, Advanced Excel and also tried to understand why am I changing t...read more
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