Lead Data Analyst

Lead Data Analyst Interview Questions and Answers

Updated 9 Jul 2025
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Asked in Subex

2d ago

Q. 1.Difference between loc and iloc in pandas. SQL queries 2.Pivot the table. 3.find the cummaltive sum of orders till the current day. Scenario based questions like - How will you address decline in revenue. Be...

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Ans.

loc and iloc are two methods in pandas used for selecting data from a DataFrame based on labels or integer index.

  • loc is label-based, meaning you specify the row and column labels to select data

  • iloc is integer index-based, meaning you specify the row and column indices to select data

  • Example: df.loc['row_label', 'column_label'] vs df.iloc[row_index, column_index]

Asked in Wells Fargo

2d ago

Q. What data is relevant for any derivative transaction?

Ans.

Data relevant for derivative transactions include underlying asset, contract terms, market price, expiration date, and counterparty information.

  • Underlying asset (e.g. stock, commodity, currency)

  • Contract terms (e.g. type of derivative, quantity, strike price)

  • Market price of the underlying asset

  • Expiration date of the contract

  • Counterparty information (e.g. name, creditworthiness)

Asked in S&P Global

3d ago

Q. What are the common reasons employees quit their jobs?

Ans.

Employees often quit due to lack of growth, poor management, work-life imbalance, and inadequate compensation.

  • Limited career advancement opportunities can lead to frustration; for example, an employee may leave if they see no path to promotion.

  • Poor management practices, such as micromanagement or lack of support, can drive employees away; for instance, a manager who fails to recognize achievements.

  • A poor work-life balance, where employees feel overworked or stressed, can resu...read more

6d ago

Q. Explain how data is analyzed.

Ans.

Data analysis involves cleaning, transforming, and interpreting data to extract meaningful insights.

  • Data is collected from various sources such as databases, surveys, or sensors

  • The data is cleaned to remove errors, duplicates, and inconsistencies

  • Data is transformed and structured for analysis using tools like Excel, Python, or R

  • Statistical techniques and machine learning algorithms are applied to identify patterns and trends

  • Visualizations such as charts or graphs are created ...read more

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