HSBC Electronic Data Processing Interview Questions, Process, and Tips

Good questions on aptitude and statistics were asked

Group discussion were held

Q1. Difference between pop and remove in python
Ans. 
pop() removes and returns the last element of a list, while remove() removes the first occurrence of a specified value.
• pop() modifies the original list, while remove() only removes the specified value

• pop() requires an index as an argument, while remove() requires the value to be removed

• pop() returns the removed element, while remove() does not return anything
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Q2. Difference between shallow copy and deep copy
Ans. 
Shallow copy only copies the references of objects, while deep copy creates new copies of objects.
• Shallow copy creates a new object but does not create copies of nested objects.

• Deep copy creates new copies of all nested objects.

• Shallow copy is faster and more memory efficient, but changes to nested objects affect both copies.

• Deep copy is slower and uses more memory, but changes to nested objects do not affect the origi
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Based on the results of the psychometric test.

Q1. What do you know about the process knowledge related to the position you are applying for?
Ans. 
Process knowledge related to Senior Operations Analyst position includes understanding of operational procedures, data analysis, and process improvement.
• Understanding of operational procedures and workflows

• Ability to analyze data and identify trends

• Experience with process improvement methodologies such as Six Sigma or Lean

• Knowledge of project management principles

• Familiarity with relevant software and tools like Excel,
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General language and mathematics questions

On the given topic, need to discuss in front of everyone with loud and clear voice

Q1. Operations test / technical test
Ans. As asked
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Q1. Payscale negotiatins
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General aptitude and reasoning questions

Q1. Asked about projects and experience, then later asked few puzzles and basic python questions
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Q1. Discussions about pay scale, expectations and work details
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Q1. Explain linear regression, cost function, Ridge and Lasso regression
Ans. 
Linear regression is a statistical technique to model the relationship between a dependent variable and one or more independent variables.
• Linear regression is used to predict a continuous outcome variable based on one or more predictor variables.

• The cost function measures the difference between the predicted values and the actual values in linear regression.

• Ridge regression is a regularization technique that adds a pen...read more
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Q2. Explain missing value treatment
Ans. 
Missing value treatment refers to the process of handling and managing missing values in a dataset.
• Missing values can occur when data is not collected or recorded for certain observations or variables.

• Common methods for missing value treatment include deletion, imputation, and prediction.

• Deletion involves removing observations or variables with missing values, but this can lead to loss of information.

• Imputation replace...read more
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Q3. Difference between mean, median and mode
Ans. 
Mean is the average of a set of numbers, median is the middle value, and mode is the most frequently occurring value.
• Mean is calculated by summing all the values and dividing by the number of values.

• Median is the middle value when the numbers are arranged in ascending or descending order.

• Mode is the value that appears most frequently in the set of numbers.

• Mean is affected by outliers, while median and mode are not.

• For ...read more
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Questions around Anti Money Laundering

Q1. Culture fit round to see if my goals are aligned to company's goal
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Q2. Where do you see yourself in 5 years?
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Credit Analysis skills along with nuances of credit underwriting

Q1. Credit, Risk, Financial Statement
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Q1. Genuine questions apart from worl
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