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Walmart Data Scientist Interview Questions, Process, and Tips for Experienced

Updated 27 Jul 2024

Top Walmart Data Scientist Interview Questions and Answers for Experienced

  • Q1. How can you tune the hyper parameters of XGboost,Random Forest,SVM algorithm?
  • Q2. What do these hyper parameters in the above mentioned algorithms actually mean?
  • Q3. How to fit a time series model? State all the steps you would follow.
View all 6 questions

Walmart Data Scientist Interview Experiences for Experienced

4 interviews found

Interview experience
2
Poor
Difficulty level
-
Process Duration
-
Result
-
Round 1 - Coding Test 

3 Leet code mediums in 30 mins.

Round 2 - Technical 

(3 Questions)

  • Q1. 5 ML questions in 10 mins
  • Q2. 5 Stats question in 10 mins
  • Q3. 3 LC mediums in 30 minutes
  • Ans. 

    LC mediums refer to LeetCode mediums, which are medium difficulty coding problems on the LeetCode platform.

    • LC mediums are coding problems with medium difficulty level on LeetCode platform.

    • Solving 3 LC mediums in 30 minutes requires good problem-solving skills and efficient coding techniques.

    • Examples of LC mediums include 'Longest Substring Without Repeating Characters' and 'Container With Most Water'.

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Pray

Data Scientist Interview Questions & Answers

user image Navina Kaur

posted on 17 Jun 2024

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed before Jun 2023. There were 3 interview rounds.

Round 1 - One-on-one 

(1 Question)

  • Q1. Resume related questions with the hiring manager
Round 2 - Coding Test 

Python for Data Science basics

Round 3 - Case Study 

Optimization case study

Data Scientist Interview Questions Asked at Other Companies for undefined

asked in Coforge
Q1. coding question of finding index of 2 nos. having total equal to ... read more
asked in Walmart
Q2. How can you tune the hyper parameters of XGboost,Random Forest,SV ... read more
Q3. How did you prevent your model from overfitting ? What did you do ... read more
asked in Walmart
Q4. What do these hyper parameters in the above mentioned algorithms ... read more
asked in Nielsen
Q5. Write pandas query to separate the names as first and last name f ... read more
Interview experience
4
Good
Difficulty level
Moderate
Process Duration
Less than 2 weeks
Result
Selected Selected

I applied via Referral and was interviewed before Sep 2022. There were 6 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Keep your resume crisp and to the point. A recruiter looks at your resume for an average of 6 seconds, make sure to leave the best impression.
View all tips
Round 2 - Technical 

(1 Question)

  • Q1. All the questiones were asked around CV. Mostly problems related to ML, DL, NLP, mathematics behind the algorithms, case studies, alternate solutions of popular use cases etc.
Round 3 - Technical 

(1 Question)

  • Q1. Same as round 1 but this round involved a lot of mathematical functions and derivations of several aspects of ML and DL. Also a lot of case studies were involved
Round 4 - Coding Test 

Had to share my screen and they gave live problems to test my knowledge in python

Round 5 - One-on-one 

(1 Question)

  • Q1. Call with hiring manager mostly on my CV and a lot of case studies.
Round 6 - HR 

(1 Question)

  • Q1. Typical HR round questions

I was interviewed in Apr 2021.

Interview Questionnaire 

9 Questions

  • Q1. How can you tune the hyper parameters of XGboost,Random Forest,SVM algorithm?
  • Ans. 

    Hyperparameters of XGBoost, Random Forest, and SVM can be tuned using techniques like grid search, random search, and Bayesian optimization.

    • For XGBoost, important hyperparameters to tune include learning rate, maximum depth, and number of estimators.

    • For Random Forest, important hyperparameters to tune include number of trees, maximum depth, and minimum samples split.

    • For SVM, important hyperparameters to tune include ke...

  • Answered by AI
  • Q2. What do these hyper parameters in the above mentioned algorithms actually mean?
  • Ans. 

    Hyperparameters are settings that control the behavior of machine learning algorithms.

    • Hyperparameters are set before training the model.

    • They control the learning process and affect the model's performance.

    • Examples include learning rate, regularization strength, and number of hidden layers.

    • Optimizing hyperparameters is important for achieving better model accuracy.

  • Answered by AI
  • Q3. Difference between Ridge and LASSO and their geometric interpretation.
  • Ans. 

    Ridge and LASSO are regularization techniques used in linear regression to prevent overfitting.

    • Ridge adds a penalty term to the sum of squared errors, which shrinks the coefficients towards zero but doesn't set them exactly to zero.

    • LASSO adds a penalty term to the absolute value of the coefficients, which can set some of them exactly to zero.

    • The geometric interpretation of Ridge is that it adds a constraint to the size...

  • Answered by AI
  • Q4. How to fit a time series model? State all the steps you would follow.
  • Ans. 

    Steps to fit a time series model

    • Identify the time series pattern

    • Choose a suitable model

    • Split data into training and testing sets

    • Fit the model to the training data

    • Evaluate model performance on testing data

    • Refine the model if necessary

    • Forecast future values using the model

  • Answered by AI
  • Q5. RNN,CNN and difference between these two.
  • Ans. 

    RNN and CNN are neural network architectures used for different types of data.

    • RNN is used for sequential data like time series, text, speech, etc.

    • CNN is used for grid-like data like images, videos, etc.

    • RNN has feedback connections while CNN has convolutional layers.

    • RNN can handle variable length input while CNN requires fixed size input.

    • Both can be used for classification, regression, and generation tasks.

  • Answered by AI
  • Q6. Two Case studies related to optimisation. One was cost optimization and other one was Revenue optimization. What data would you look at to solve all these. How would you form the objective function.
  • Ans. 

    Answering a question on data and objective function for cost and revenue optimization case studies.

    • For cost optimization, look at data related to expenses, production costs, and resource allocation.

    • For revenue optimization, look at data related to sales, customer behavior, and market trends.

    • Objective function for cost optimization could be minimizing expenses while maintaining quality.

    • Objective function for revenue opt...

  • Answered by AI
  • Q7. Live coding on Time Series Modelling
  • Q8. There were some HR questions as well like how would you make someone understand the difference between a classification problem and a prediction problem.
  • Q9. Where do you see yourself in 3 years?

Interview Preparation Tips

Interview preparation tips for other job seekers - I was asked questions from almost every field in Data Science. One has to be very technically sound and has to have clear understanding of all the ML algorithms.

If you don't know something,better to mention it clearly.

All the very best!

Skills evaluated in this interview

Walmart interview questions for designations

 Senior Data Scientist

 (1)

 Data Scientist Staff

 (1)

 Senior Data Analyst

 (6)

 Senior Manager Analytics

 (1)

 Data Engineer

 (8)

 Data Analyst

 (4)

 Senior Data Engineer

 (4)

 Data Entry jobs

 (1)

Data Scientist Jobs at Walmart

View all

Interview questions from similar companies

Interview Questionnaire 

1 Question

  • Q1. What PCA, Decision tree and computer vision
  • Ans. 

    PCA is a dimensionality reduction technique, decision tree is a classification algorithm, and computer vision is a field of study focused on enabling computers to interpret and understand visual information.

    • PCA is used to reduce the number of variables in a dataset while retaining the most important information.

    • Decision trees are used to classify data based on a set of rules and conditions.

    • Computer vision involves usin...

  • Answered by AI

Skills evaluated in this interview

I applied via Approached by Company and was interviewed before Sep 2021. There were 3 interview rounds.

Round 1 - Resume Shortlist 
Pro Tip by AmbitionBox:
Don’t add your photo or details such as gender, age, and address in your resume. These details do not add any value.
View all tips
Round 2 - Aptitude Test 

Explain dynamic programming with memoization

Round 3 - HR 

(2 Questions)

  • Q1. Where are you from, and why are you joining the company
  • Q2. Why are you joining the company

Interview Preparation Tips

Interview preparation tips for other job seekers - First, they will ask about the breadth of your ML skills and the depth going forward

I applied via Campus Placement and was interviewed before Sep 2020. There were 3 interview rounds.

Interview Questionnaire 

1 Question

  • Q1. Nothing much technical

Interview Preparation Tips

Interview preparation tips for other job seekers - 1. Go in formals
2. Fluency in English is important (depends on interview panel)
3. Clarity on what your talking about
Interview experience
3
Average
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Not Selected

I applied via Approached by Company and was interviewed in Aug 2023. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. How can Logistic regression be applied for multiclasstext classification
  • Ans. 

    Logistic regression can be applied for multiclasstext classification by using one-vs-rest or softmax approach.

    • One-vs-rest approach: Train a binary logistic regression model for each class, treating it as the positive class and the rest as the negative class.

    • Softmax approach: Use the softmax function to transform the output of the logistic regression into probabilities for each class.

    • Evaluate the model using appropriate...

  • Answered by AI

Skills evaluated in this interview

Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via LinkedIn and was interviewed before Apr 2023. There was 1 interview round.

Round 1 - Technical 

(1 Question)

  • Q1. How does fbpropher forecasting model works and how is can be used to forecsst trafffic
  • Ans. 

    fbprophet is a forecasting model developed by Facebook that uses time series data to make predictions.

    • fbprophet is an open-source forecasting tool developed by Facebook's Core Data Science team.

    • It is based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.

    • fbprophet can be used to forecast traffic by providing historical data on traffic patterns and usi...

  • Answered by AI

Interview Preparation Tips

Interview preparation tips for other job seekers - Thourough with maths of forecasting techniques and parameter tuning
Interview experience
5
Excellent
Difficulty level
Moderate
Process Duration
2-4 weeks
Result
Selected Selected

I applied via Company Website and was interviewed before Jul 2023. There were 3 interview rounds.

Round 1 - Coding Test 

Binary tree question was asked

Round 2 - Technical 

(1 Question)

  • Q1. Several tech question related to past projects and random forest etc were asked.
Round 3 - HR 

(1 Question)

  • Q1. Tell me about yourself and several other questions

Walmart Interview FAQs

How many rounds are there in Walmart Data Scientist interview for experienced candidates?
Walmart interview process for experienced candidates usually has 3-4 rounds. The most common rounds in the Walmart interview process for experienced candidates are Technical, Coding Test and One-on-one Round.
How to prepare for Walmart Data Scientist interview for experienced candidates?
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 Walmart. The most common topics and skills that interviewers at Walmart expect are Machine Learning, Python, Information Technology, SQL and Data Science.
What are the top questions asked in Walmart Data Scientist interview for experienced candidates?

Some of the top questions asked at the Walmart Data Scientist interview for experienced candidates -

  1. How can you tune the hyper parameters of XGboost,Random Forest,SVM algorith...read more
  2. What do these hyper parameters in the above mentioned algorithms actually mea...read more
  3. How to fit a time series model? State all the steps you would follo...read more

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Walmart Data Scientist Interview Process for Experienced

based on 3 interviews

Interview experience

3.7
  
Good
View more
Walmart Data Scientist Salary
based on 147 salaries
₹18 L/yr - ₹60 L/yr
160% more than the average Data Scientist Salary in India
View more details

Walmart Data Scientist Reviews and Ratings

based on 10 reviews

3.0/5

Rating in categories

3.0

Skill development

3.3

Work-life balance

3.5

Salary

3.6

Job security

2.9

Company culture

2.7

Promotions

2.7

Work satisfaction

Explore 10 Reviews and Ratings
STAFF, DATA SCIENTIST

Bangalore / Bengaluru

8-14 Yrs

Not Disclosed

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