Micron Technology Data Scientist Interview Questions and Answers

Q1. How Decision tree works
Ans. 
Decision tree is a predictive modeling tool that uses a tree-like graph of decisions and their possible consequences.
• Decision tree splits data into subsets based on the value of a certain attribute

• It recursively divides data into smaller subsets until a stopping criterion is met

• Each internal node represents a decision based on an attribute, and each leaf node represents the outcome
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Q1. How pressure varies wrt temperature
Ans. 
Pressure generally increases with temperature due to the kinetic energy of gas molecules.
• Pressure is directly proportional to temperature in a closed system (Boyle's Law).

• As temperature increases, gas molecules move faster and collide with the container walls more frequently, increasing pressure.

• For example, a balloon inflated indoors may burst when taken outside on a hot day due to increased pressure from higher tempe
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Q1. What challenges you faced
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Q1. Explain about the project
Ans. 
Developed a machine learning model to predict customer churn for a telecom company
• Used historical customer data to train the model

• Implemented various classification algorithms such as logistic regression, random forest, and XGBoost

• Evaluated model performance using metrics like accuracy, precision, recall, and F1 score
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Q2. Basic SQLQuestions
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Q1. Intermediate level SQL questions
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Q2. Intermediate level python/machine learning questions
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Binary tree question was asked

Q1. Several tech question related to past projects and random forest etc were asked.
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Q1. Tell me about yourself and several other questions
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Ml algorithms ,deeplearning, nlp questioons and projects

Python basic codeing

Q1. Basic about python
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Analysis using scrapping

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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