HSBC Group Data Analyst Intern Interview Questions and Answers

Q1. Questions based on projects in the resume
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Q2. Machine learning questions
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Two basic programming questions (30 min) and reasoning/aptitude questions

Q1. How will you pull data from a table, given a time interval?
Ans. 
Use SQL query with WHERE clause to pull data from a table based on a time interval.
• Use SQL query with SELECT statement to specify the columns you want to retrieve.

• Add a WHERE clause with the condition for the time interval, using appropriate date/time functions.

• Example: SELECT * FROM table_name WHERE timestamp_column BETWEEN 'start_time' AND 'end_time';
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Q1. How would you run a business on a state level to maximize your sales?
Ans. 
To maximize sales on a state level, focus on market research, targeted marketing strategies, strong customer service, and strategic partnerships.
• Conduct market research to understand the local consumer behavior and preferences

• Implement targeted marketing strategies based on the research findings

• Provide excellent customer service to build loyalty and attract repeat business

• Form strategic partnerships with local business...read more
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Assignment on credit risk

Q1. Hyperparameter tuning
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Q1. Case study for problem solving
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Question on Probability and basic aptitude questions

Q1. Question were related to Past projects
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Q2. SQL and Excel medium level questions
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Q1. Given a variable, how to do Linear Regression?
Ans. 
Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables.
• Collect data on the variables of interest

• Plot the data to visualize the relationship between the variables

• Choose a suitable linear regression model (simple or multiple)

• Fit the model to the data using a regression algorithm (e.g. least squares)

• Evaluate the model's performance using ...read more
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Q2. How Linear Regression handles noise?
Ans. 
Linear Regression minimizes noise by fitting a line that best represents the relationship between variables.
• Linear Regression minimizes the sum of squared errors between the actual data points and the predicted values on the line.

• It assumes that the noise in the data is normally distributed with a mean of zero.

• Outliers in the data can significantly impact the regression line and its accuracy.

• Regularization techniques l...read more
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Q3. Solve two equations to find coefficients?
Ans. 
Use linear algebra to solve for coefficients in two equations.
• Set up the two equations with unknown coefficients

• Solve the equations simultaneously using methods like substitution or elimination

• Example: 2x + 3y = 10 and 4x - y = 5, solve for x and y
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Q4. Probability question on picking a red ball from Red, blue, black ball bag with replacement.
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Q1. Questions based on projects in the resume
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Q2. Machine learning questions
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Q1. How do you define model Gini?
Ans. 
Model Gini is a measure of statistical dispersion used to evaluate the performance of classification models.
• Model Gini is calculated as twice the area between the ROC curve and the diagonal line (random model).

• It ranges from 0 (worst model) to 1 (best model), with higher values indicating better model performance.

• A Gini coefficient of 0.5 indicates a model that is no better than random guessing.

• Commonly used in credit
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Q2. How to you train XG boost model
Ans. 
XGBoost model is trained by specifying parameters, splitting data into training and validation sets, fitting the model, and tuning hyperparameters.
• Specify parameters for XGBoost model such as learning rate, max depth, and number of trees

• Split data into training and validation sets using train_test_split function

• Fit the XGBoost model on training data using fit method

• Tune hyperparameters using techniques like grid search
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Python coding question and ML question

Q1. ML questions from resume + general
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Q1. Techno managerial round
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