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Wells Fargo Data Scientist Interview Questions and Answers

Updated 20 Aug 2024

Wells Fargo Data Scientist Interview Experiences

4 interviews found

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via LinkedIn and was interviewed in Jul 2024. There were 3 interview rounds.

Round 1 - Assignment 

Assignment on credit risk

Round 2 - Technical 

(1 Question)

  • Q1. Hyperparameter tuning
Round 3 - Technical 

(1 Question)

  • Q1. Case study for problem solving
Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

Python coding question and ML question

Round 2 - Technical 

(1 Question)

  • Q1. ML questions from resume + general
Round 3 - One-on-one 

(1 Question)

  • Q1. Techno managerial round

Data Scientist Interview Questions Asked at Other Companies

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Interview experience
1
Bad
Difficulty level
-
Process Duration
-
Result
-
Round 1 - One-on-one 

(1 Question)

  • Q1. How to extract numbers pre decimal point from a long list of decimalnumbers with efficiency
  • Ans. 

    Use string manipulation to efficiently extract numbers before the decimal point from a list of decimal numbers.

    • Split each decimal number by the decimal point and extract the number before it

    • Use regular expressions to match and extract numbers before the decimal point

    • Iterate through the list and extract numbers using string manipulation functions

  • Answered by AI

Skills evaluated in this interview

Interview Questionnaire 

3 Questions

  • Q1. Mainly resume based. In detail from the project.
  • Q2. Softmax vs sigmoid
  • Ans. 

    Softmax and sigmoid are both activation functions used in neural networks.

    • Softmax is used for multi-class classification problems, while sigmoid is used for binary classification problems.

    • Softmax outputs a probability distribution over the classes, while sigmoid outputs a probability for a single class.

    • Softmax ensures that the sum of the probabilities of all classes is 1, while sigmoid does not.

    • Softmax is more sensitiv...

  • Answered by AI
  • Q3. Logistics regression (multiclass)

Interview Preparation Tips

Interview preparation tips for other job seekers - Prepare the projects mentioned in your resume very well

Skills evaluated in this interview

Wells Fargo interview questions for designations

 Senior Data Scientist

 (1)

 Senior Data Analyst

 (1)

 Lead Data Analyst

 (1)

 Analytics Consultant

 (10)

 Senior Analytics Consultant

 (5)

 Analytics Manager

 (1)

 Quantitative Analyst

 (1)

 Data Analyst

 (5)

Interview questions from similar companies

Interview experience
4
Good
Difficulty level
Moderate
Process Duration
-
Result
No response

I applied via Job Portal and was interviewed in Nov 2023. There was 1 interview round.

Round 1 - One-on-one 

(5 Questions)

  • 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...

  • Answered by AI
  • 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.

  • Answered by AI
  • 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.
  • 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...

  • Answered by AI
  • 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...

  • Answered by AI

Interview Preparation Tips

Topics to prepare for Motilal Oswal Financial Services Data Scientist interview:
  • Machine Learning
  • Statistics
  • Pandas
Interview experience
4
Good
Difficulty level
Easy
Process Duration
2-4 weeks
Result
Selected Selected

I applied via IIM Jobs and was interviewed before Jun 2023. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. SQL basic questions
  • Q2. Python - pandas, numpy based questions

Interview Preparation Tips

Interview preparation tips for other job seekers - Great place to work
Interview experience
5
Excellent
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Technical 

(2 Questions)

  • 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

  • Answered by AI
  • 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

  • Answered by AI

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Not Selected

I applied via Referral and was interviewed before May 2023. There was 1 interview round.

Round 1 - Technical 

(2 Questions)

  • Q1. Self Intro and projects discussion
  • 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.

  • Answered by AI

Skills evaluated in this interview

Interview experience
3
Average
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Aptitude Test 

(1 Question)

  • 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...

  • Answered by AI
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
No response

I applied via Referral and was interviewed in Nov 2024. There were 2 interview rounds.

Round 1 - Technical 

(4 Questions)

  • Q1. Types of Chunking in data preparation in RAG
  • Q2. How Embedding works in Vector Databases
  • Q3. Explain ARIMA model
  • Q4. How can we decide to choose Linear Regression for a business problem
Round 2 - Technical 

(4 Questions)

  • Q1. What is token and it's limit for Open Source LLMs
  • Q2. Difference of a Regression and Time Series problem
  • Q3. Advantage of LSTM over RNN
  • Q4. Performance Metrics for Logistic Regression

Wells Fargo Interview FAQs

How many rounds are there in Wells Fargo Data Scientist interview?
Wells Fargo interview process usually has 2-3 rounds. The most common rounds in the Wells Fargo interview process are Technical, One-on-one Round and Coding Test.
How to prepare for Wells Fargo Data Scientist interview?
Go through your CV in detail and study all the technologies mentioned in your CV. Prepare at least two technologies or languages in depth if you are appearing for a technical interview at Wells Fargo. The most common topics and skills that interviewers at Wells Fargo expect are Monitoring, Operations, Analytical, Machine Learning and Risk Management.
What are the top questions asked in Wells Fargo Data Scientist interview?

Some of the top questions asked at the Wells Fargo Data Scientist interview -

  1. How to extract numbers pre decimal point from a long list of decimalnumbers wit...read more
  2. Softmax vs sigm...read more
  3. Mainly resume based. In detail from the proje...read more

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Wells Fargo Data Scientist Interview Process

based on 3 interviews

Interview experience

2.7
  
Poor
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Wells Fargo Data Scientist Salary
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₹19.3 L/yr - ₹45 L/yr
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3.0/5

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2.5

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3.9

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