Wells Fargo Analytics Manager Interview Questions and Answers

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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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
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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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I was asked Python, sql, coding questions

Case study on how would you identify the total number of footfall on a airport

Q1. SQL queries regarding your project
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Q2. Pratice joining concepts
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Q3. Regarding end to end intercation with your project manager
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Q4. ETL process and tableau concepts
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Q5. Dashboard related to Tableau
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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. Logistic regression, modeling experience, choosing best model, SQL.. Find the third transaction of customer from dataset
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Q1. Introduction by my self
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Q2. Pyspark related getting the column names
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Q1. Sorting Question
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