SBI Securities Data Analyst Intern Interview Questions and Answers

Q1. Detailed project questions
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Q2. Explain completed gen ai project
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Developed a generative AI model to create realistic images of fictional characters.
• Used GANs (Generative Adversarial Networks) to generate new images based on existing data.

• Trained the model on a dataset of character images from various sources.

• Implemented techniques like style transfer to enhance the diversity and creativity of generated images.

• Evaluated the model's performance based on image quality metrics and user
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Q1. Talked about previous experience in detail.
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Q2. Asked some case studies regarding their products
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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. What is Gradient Descents?
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Gradient descent is an optimization algorithm used to minimize a function by iteratively moving in the direction of steepest descent.
• Gradient descent is used to find the minimum of a function by taking steps proportional to the negative of the gradient at the current point.

• It is commonly used in machine learning to optimize the parameters of a model by minimizing the loss function.

• There are different variants of gradie...read more
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Q2. What is LSTM?, and what are the gates in it?
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LSTM (Long Short-Term Memory) is a type of recurrent neural network designed to handle long-term dependencies.
• LSTM has three gates: input gate, forget gate, and output gate.

• Input gate controls the flow of information into the cell state.

• Forget gate decides what information to discard from the cell state.

• Output gate determines the output based on the cell state.
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Q3. They gave me a link to dataset and started saying the operations to apply on that. E.g, value_counts, null_values, fill the values with mean,etc.
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Q4. What is t-test? What is Mean, Median and Mode and where to use these?
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T-test is a statistical test used to determine if there is a significant difference between the means of two groups.
• Mean is the average of a set of numbers, median is the middle value when the numbers are ordered, and mode is the most frequently occurring value.

• Mean is sensitive to outliers, median is robust to outliers, and mode is useful for categorical data.

• T-test is used to compare means of two groups, mean is used...read more
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Q5. What is RANDOM FOREST ?
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Random Forest is an ensemble learning method used for classification and regression tasks.
• Random Forest is a collection of decision trees that are trained on random subsets of the data.

• Each tree in the forest makes a prediction, and the final prediction is the average (regression) or majority vote (classification) of all trees.

• Random Forest helps reduce overfitting and improve accuracy compared to a single decision tre...read more
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Q1. Tell me about your projects
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Q2. What do you know about mutual funds
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Mutual funds are investment vehicles that pool money from multiple investors to invest in a diversified portfolio of securities.
• Mutual funds are managed by professional fund managers who make investment decisions on behalf of the investors.

• Investors can buy shares of mutual funds, which represent their ownership in the fund's portfolio.

• Mutual funds offer diversification, liquidity, and professional management to invest...read more
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Q1. Do you have prior experience with ML
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Q2. What are your long term plans
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Q1. Explain any Data Science project
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Developed a predictive model to forecast customer churn for a telecommunications company.
• Identified key features such as customer tenure, monthly charges, and service usage

• Collected and cleaned data from customer databases

• Built a machine learning model using logistic regression or random forest algorithms

• Evaluated model performance using metrics like accuracy, precision, and recall

• Provided actionable insights to reduce
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Q2. Types of Error in Statistics
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Types of errors in statistics include sampling error, measurement error, and non-sampling error.
• Sampling error occurs when the sample does not represent the population accurately.

• Measurement error is caused by inaccuracies in data collection or measurement instruments.

• Non-sampling error includes errors in data processing, analysis, and interpretation.

• Examples: Sampling error - selecting a biased sample, Measurement err...read more
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Q3. Types of Machine learning models
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Types of machine learning models include supervised learning, unsupervised learning, and reinforcement learning.
• Supervised learning: Models learn from labeled data, making predictions based on past examples (e.g. linear regression, support vector machines)

• Unsupervised learning: Models find patterns in unlabeled data, clustering similar data points together (e.g. k-means clustering, PCA)

• Reinforcement learning: Models le...read more
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Q4. Functions of pandas library, such as get_dummies()
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get_dummies() function in pandas library is used to convert categorical variables into dummy/indicator variables.
• get_dummies() function creates dummy variables for categorical columns in a DataFrame.

• It converts categorical variables into numerical representation for machine learning models.

• Example: df = pd.get_dummies(df, columns=['column_name'])
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Q1. Types of Chunking in data preparation in RAG
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Q2. How Embedding works in Vector Databases
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Q3. Explain ARIMA model
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Q4. How can we decide to choose Linear Regression for a business problem
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Q1. What is token and it's limit for Open Source LLMs
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Q2. Difference of a Regression and Time Series problem
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Q3. Advantage of LSTM over RNN
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Q4. Performance Metrics for Logistic Regression
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