PayPal Data Analyst 2 Interview Questions and Answers

Q1. SQL Joins and remove duplicates
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Q2. Function to create a transaction bin column
Ans. 
Create a function to generate a transaction bin column based on transaction amounts.
• Create bins based on transaction amounts (e.g. $0-$100, $101-$200, etc.)

• Use pandas cut() function in Python to create bins

• Assign bin labels to the transactions based on the bin ranges
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Sql, python, statistical questions

Q1. How daily work looks like?
Ans. 
Daily work involves analyzing data, creating reports, and communicating findings to stakeholders.
• Reviewing and cleaning data sets

• Creating visualizations and dashboards

• Conducting statistical analysis

• Communicating insights to non-technical stakeholders
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Q2. Most ise tools?
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Some of the most commonly used tools for data analysis include Excel, Python, R, Tableau, and SQL.
• Excel is widely used for data manipulation and analysis.

• Python and R are popular programming languages for data analysis and machine learning.

• Tableau is a powerful data visualization tool.

• SQL is essential for querying databases and extracting data.
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4 sql tasks on 3 tables. Joins, subqueries

Q1. Sql questions on windows functions, subquery
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Q2. Guesstimmate on how many cricket bat is solved in a year
Ans. 
It is difficult to accurately estimate the number of cricket bats sold in a year without specific data.
• The number of cricket bats sold in a year can vary based on factors such as seasonality, popularity of cricket, and market trends.

• One approach to estimate could be to consider the total population of cricket-playing countries and the average number of bats owned by players.

• Another approach could be to look at the sale...read more
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Q1. Short cut keys of tools
Ans. 
Short cut keys are keyboard shortcuts that allow users to quickly perform actions in various tools.
• Ctrl + C: Copy

• Ctrl + V: Paste

• Ctrl + X: Cut

• Ctrl + Z: Undo

• Ctrl + S: Save

• Ctrl + P: Print
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Q1. Project explanation in brief manner
Ans. 
Developed a predictive model to forecast sales based on historical data
• Collected and cleaned historical sales data

• Performed exploratory data analysis to identify trends and patterns

• Built and trained machine learning model using regression techniques

• Evaluated model performance using metrics like RMSE and MAE
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Q1. Basic questions about resume
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Q1. Workplace adjustment questions
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Q2. Are you willing to work extra hours
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Q1. DBSCAN Clustering
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Q2. How does current work helps solving use cases for PayU
Ans. 
My current work involves analyzing transaction data to identify patterns and trends, which can help PayU optimize their payment processing services.
• Analyzing transaction data to identify fraudulent activities and improve security measures for PayU

• Developing predictive models to forecast transaction volumes and optimize payment processing times

• Utilizing machine learning algorithms to personalize user experiences and inc...read more
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Q1. Internal external tables
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Q2. MySQL questions
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Data Coding, 1hr, series of questions in excel