FIN Infocom Data Scientist 2 Interview Questions and Answers

Q1. What is the pivot table in Excel
Ans. 
A pivot table in Excel is a data summarization tool that allows you to reorganize and summarize selected columns and rows of data.
• Allows users to summarize and analyze large datasets

• Can easily reorganize data by dragging and dropping fields

• Provides options to calculate sums, averages, counts, etc. for data

• Helps in creating interactive reports and charts

• Useful for identifying trends and patterns in data
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Q2. A pivot table is used to summarize...........etc.
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Based on my CV, they assigned me a task related to data migration.

Q1. Project reviews
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Q2. Attendance regarding
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Q1. What is the full form of ETL?
Ans. 
ETL stands for Extract, Transform, Load. It is a process used in data warehousing to extract data from various sources, transform it into a consistent format, and load it into a target database.
• ETL stands for Extract, Transform, Load

• Extract: Involves extracting data from various sources such as databases, applications, and files

• Transform: Involves cleaning, filtering, and transforming the extracted data into a consiste...read more
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Q2. ETL Full form is Exact, Transform, Load.
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Q1. Why do we hire you?
Ans. 
I have a strong background in data analysis, machine learning, and problem-solving skills that make me a valuable asset to your team.
• Extensive experience in data analysis and machine learning techniques

• Proven track record of solving complex problems using data-driven approaches

• Strong communication and collaboration skills demonstrated through team projects and internships
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Q2. What contributions should you make?
Ans. 
As a Data Science Intern, I should contribute by analyzing data, developing models, and providing insights to drive decision-making.
• Analyze data to identify trends and patterns

• Develop predictive models to forecast outcomes

• Provide actionable insights to stakeholders

• Contribute to data-driven decision-making processes
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Q1. Mostly about projects ml, nlp, python code would be asked
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Q1. It would be focused on technical stuff in detail ml, nlp, deployments etc
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Q1. Organisation fit
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Q1. No question was asked
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Q2. Same as above, zero questions were asked
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Q1. What is overfitting in machine learning?
Ans. 
Overfitting occurs when a machine learning model learns the training data too well, including noise and outliers, leading to poor generalization on new data.
• Overfitting happens when a model is too complex and captures noise in the training data.

• It leads to poor performance on unseen data as the model fails to generalize well.

• Techniques to prevent overfitting include cross-validation, regularization, and early stopping.

• ...read more
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Q2. Overfitting accurs when a model learns the details.......etc
Ans. 
Overfitting occurs when a model learns the details and noise in the training data to the extent that it negatively impacts the model's performance on new data.
• Overfitting happens when a model is too complex and captures noise in the training data.

• It leads to poor generalization and high accuracy on training data but low accuracy on new data.

• Techniques to prevent overfitting include cross-validation, regularization, and...read more
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