Wells Fargo Data Scientist Interview Questions and Answers for Experienced

Q1. Difference between CNN and MLP
Ans. 
CNN is used for image recognition while MLP is used for general classification tasks.
• CNN uses convolutional layers to extract features from images while MLP uses fully connected layers.

• CNN is better suited for tasks that require spatial understanding like object detection while MLP is better for tabular data.

• CNN has fewer parameters than MLP due to weight sharing in convolutional layers.

• CNN can handle input of varying
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Q1. Work done in previous companty
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Developed machine learning models to predict customer churn and optimize marketing campaigns.
• Built predictive models using Python and scikit-learn

• Utilized SQL to extract and manipulate data for analysis

• Collaborated with cross-functional teams to implement data-driven solutions
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Q1. SQL basic questions
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Q2. Python - pandas, numpy based questions
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Q1. What is Gradient Descents?
Ans. 
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?
Ans. 
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?
Ans. 
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 ?
Ans. 
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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I was asked Python, sql, coding questions

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

Q1. ML concepts , regression, regularization etc
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Q1. Self Intro and projects discussion
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Q2. Feature selection methods
Ans. 
Feature selection methods help in selecting the most relevant features for building predictive models.
• Feature selection methods aim to reduce the number of input variables to only those that are most relevant.

• Common methods include filter methods, wrapper methods, and embedded methods.

• Examples include Recursive Feature Elimination (RFE), Principal Component Analysis (PCA), and Lasso regression.
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Q1. Central Limit Theorem
Ans. 
Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases.
• The Central Limit Theorem is essential in statistics as it allows us to make inferences about a population based on a sample.

• It states that regardless of the shape of the population distribution, the sampling distribution of the sample mean will be approximately normally distribut...read more
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