Interview Guide Jun 20
Jun 203 rounds
A Walmart Data Scientist plays a crucial role in the company's operations by using data to inform and drive business decisions. They use advanced analytical methods to extract insights from large sets of structured and unstructured data, and use these insights to improve performance and drive growth.
One key responsibility of a Walmart Data Scientist is to help the company understand consumer behavior and preferences. They do this by analyzing data from customer transactions, surveys, and social media, and use this information to inform marketing and sales strategies. They also help optimize pricing and inventory management by analyzing data on sales trends, consumer demand, and supply chain logistics.
Walmart hires for Data Scientist roles across the company and offers different levels of seniority depending on the scope and expected impact of the role. They have opportunities for Senior and Staff level positions, as well as openings for Machine Learning and Computer Vision Engineers.
Another important role of a Walmart Data Scientist is to help improve the efficiency and effectiveness of the company's operations. They use data and advanced analytics to identify inefficiencies in the supply chain, and work with other teams to implement solutions. They also use data to improve the performance of the company's website and mobile apps, as well as to inform the design of new products and services.
The examples we’ve outlined above are just a few of the key value-adds that Data Scientists drive at Walmart. There are plenty of others which we haven’t covered here; but we hope this gives you a flavor for what the role could look like.
How to Apply for a Data Scientist Job at Walmart?
Check out Walmart’s career page and browse through the Data Scientist job listings. When you find a role that interests you, be sure to read through the job requirements and qualifications carefully to ensure you meet the criteria. If you have any connections within the company, consider reaching out to them for a referral as it highly increases your chance. When you apply, make sure to tailor your resume to align with the qualifications listed in the job posting. This will help you stand out from other applicants.
And if you need help with customizing your resume specifically for Walmart (or for that matter, any other company), Prepfully provides resume review services by experienced recruiters in your target company that can give you feedback on your resume. It's worth noting that the application process may vary depending on the position and location, and the company may conduct additional assessments or interviews as part of the selection process.
Responsibilities of a Data Scientist at Walmart
The responsibilities of a data scientist at Walmart across roles can broadly be seen as-
- Identifying patterns and trends in complex data sets to inform business decisions.
- Using advanced analytics and statistical techniques to analyze data from multiple sources.
- Use computer vision techniques to create advanced deep learning models for 2D/3D image generation and synthesis, image classification, scene segmentation, object detection, keypoint detection. For instance, they’ve recently hired a bunch of Computer Vision scientists for their AR/VR explorations.
- Perform hands-on modeling and complex analyses using Python, SQL and R.
- Communicating insights and recommendations to stakeholders in a clear and actionable manner.
- Building and maintaining models to support forecasting, prediction, and optimization (for instance, forecasting demand at a product level).
- Continuously monitoring and evaluating the performance of models and data-driven solutions (for instance, in their recommender engine; their sorting engine etc).
Skills and Qualifications needed for Data Scientists at Walmart
Here are some skills and qualifications that will help you excel in your Data Science interviews at Walmart. One thing to note here is that the degree qualification (bachelor’s/ masters’) is different for every role.
- It's beneficial to have at least 5+ years of experience in Data Science roles, which can help you stand out from other candidates. Along with this, having previous work experience where you can demonstrate that you’ve used SQL, Python and/or R can also help your profile.
- Familiarity with advertising, measurement, and digital marketing analytics can often be a major advantage over other candidates.
- Strong coding skills, database knowledge and experience with cloud computing services such as GCP, AWS, or Azure is another thing which can help candidates stand out.
- Understanding of causal inferencing, multi-variate testing & design, A/B testing & design, descriptive analytics, and regression analysis is very important for some Data Scientist roles.
- Experience with big data technologies such as Hive, Hadoop, PySpark, BigQuery and modern data visualization tools like Tableau, ThoughtSpot, Looker, PowerBI, etc. can be an advantage.
- Knowledge of Machine Learning and Deep Learning libraries like scikit-learn, pytorch, tensorflow, numpy is also something we’ve seen some roles explicitly call out in their requirements.
- Experience in statistical methods and advanced modeling techniques (e.g. - SVM, Random Forest, Bayesian inference, graph models, NLP, Computer Vision, neural networks, etc.) along with the optimization and Operational Research techniques can be an added value.
It's important to keep in mind that this list is not exhaustive, and the requirements and qualifications may vary depending on the position and location. It's always best to check the job description and requirements on Walmart's Career page before you apply for the role.
As a part of the Walmart Data Scientist interview, the candidate will need to go through multiple interview rounds. The interview process and questions may differ for different positions and roles.
1. Phone Screening - The first round is to have a quick discussion about your work experiences and the roles you’ve had in the past company. The standard phone screen is typically taken by a Recruiter from HR. However - lots of Prepfully candidates have reported that this is often followed up by the culture fit interview with a Hiring Manager or Senior Manager, right after the Recruiter round. Their view was that the recruiter round was a “Screener” for this Manager round. This seems to be a process unique to Walmart.
2. The second round will comprise multiple technical rounds and it depends on the role and position that you are applying for. Depending on the role and the position, candidates have reported facing technical rounds like ML round, coding questions on HackerRank and even a dataset challenge. Some candidates have also reported working on a take-home case study with a subsequent follow-up interview that expects you to discuss everything you did in the case study, along with being able to reproduce the results.
3. The final round will usually be an interview with a senior data scientist. The questions asked here will be a combination of technical and behavioral questions. The technical questions will be heavily focused on statistics, probability and ML algorithms. On the other hand, the behavioral questions will help the interviewer understand your motivations, background, and ways of working better.
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Check out video guide that delves into the interview process and provides valuable tips tailored to each round of the interview.
You will have a conversation that focuses on assessing if your skills align with the requirements of the job of Walmart Data Scientist. The interviewer may ask you some informal questions about your experiences and abilities in order to get a better understanding of how you may fit into the Data Scientist role at Walmart. Some candidates have also reported giving a culture fit interview after the initial phone screening which is usually with a Hiring Manager or Senior Manager. This interview will be about your values and behavior fit and you will be tested on whether they align with the company or not.
- Why do you want to join Walmart?
- Why do you think you will be a good fit for the role?
- How many years of experience do you have in data science?
- What is your understanding of data science?
- What are you passionate about?
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You will face different cases of technical interviews depending on the role and the position. Let’s look at those different cases:
Coding Round - This will consist of several multiple choice questions and will have a few coding questions which will test your programming skills in SQL, Python and R.
ML Round - If you are applying for a specific role like ML Engineer, you are most likely to encounter this round. They will test you on basic ML algorithms, probability, statistics and ML system design. They will also have a project discussion on a project that you may have worked on.
Dataset Challenge - This will be a take home assessment where you will be given a dataset and then you have to build a simple ML model. For example - Build a simple ML model for binary classification and examine the classifier performance. There will also be some follow up questions about the pre-processing techniques that you used.
Case Study - You will be given a case study to work on and there will be a subsequent follow-up interview that expects you to discuss everything you did in the case study, along with being able to reproduce the results.
- What is Random forest?
- Given a dataset, what would be the output of the k-means algorithm?
- Describe a previous project of your choice, frame and solve a problem given a scenario.
- What is CNN?
- Suppose you roll a die and earn whatever face you get. What is the expected return? Now suppose you have a chance to roll a second die. If you roll, you forfeit your earnings from the first round. When should you roll the second time?
- Is the R-square measure sufficient for linear regression analysis? What if the r-square value is low, does this mean that the fit is not good enough?
- What is p-value?
- Difference between supervised, unsupervised and reinforcement learning?
- Describe how the attention mechanism works in neural networks.
- Write a SQL query for the average transaction amount for customers who have made more than 10 purchases in the last 90 days?
- Join two sorted arrays to form another sorted array.
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The final stage of the Walmart Data Scientist interview process involves an interview with a senior data scientist. This interview will include both technical and behavioral questions to evaluate your qualifications and how you align with the role and company. The technical questions may include topics such as statistics, probability, and machine learning algorithms, which will help the interviewer gauge your expertise in these areas. Additionally, the interviewer may also ask behavioral questions to gain a better understanding of your motivations, work style, and how you may fit into the team and company culture. This is an important opportunity for the interviewer to assess if you are a good match for the role and the company and for you to ask any questions you may have about the role or the company.
- Tell me about an accomplishment that you are proud of.
- Find longest substring without repeated characters.
- What are SQL window functions? Explain aggregation and joins.
- Solve a convex optimization problem.
- List out optimization algorithms.
- How does simplex work?
- How do you handle a million variables in optimization?
- What is the difference between Ridge and Lasso?
When you are preparing for a Walmart Data Scientist Interview - we’d recommend keeping these things in mind:
- Have working knowledge of SQL window functions, aggregation and joins.
- Make sure you have experience with Computer Vision and NLP techniques along with basic ML and DL algorithms.
- Familiarity with Azure, GCP and AWS is important as cloud computing plays a major role in being a data scientist.
- Learn about ML System Design in detail. You should be able to conceptually explain and build the end to end design for a fully scaled ML system within the space of a 30 min interview. This part often takes a lot of practice - we’d recommend doing a mock with an ML Engineer on Prepfully for this round, to check your readiness level.
- It is important to have worked on optimization problems as there will be many questions about it.
- R programming can be an additional skill to make your case in the interview.
- In Behavioral questions, your interviewer wants to understand your cultural fit for Walmart. To make the most of this opportunity, take some time to reflect on your background and think about what specifically attracts you to the company and the work that they do. The goal is to present yourself as a strong cultural fit for Walmart. We’d recommend having a look at their company values (link) and aligning your stories with these. For instance, Walmart explicitly calls out “Customer”, “Respect”, “Excellence” and “Integrity” within its values. So you should think of examples of where you’ve optimized relentlessly for a specific customer; or demonstrated your ability to “do the right thing” and thereby showing your integrity.
- Be clear with your technical knowledge required to fit into the role of data scientist job at Walmart. Ensure you have practice in advance for the technical questions and rounds.
The interview process for a Data Scientist role at Walmart typically includes 3 primary rounds - a phone screening, followed by technical interview rounds, and the final interview round to conclude. During the phone screening, the interviewer will assess your qualifications, experience and alignment with the role. The technical interview rounds will include several rounds and will focus on your data science and programming abilities and is likely to include a coding test. The final interview will include a mix of behavioral and technical questions. The goal of this process is to give the interviewer a well-rounded understanding of your skills, background, and fit for the role, so be sure to come prepared and ready to showcase your qualifications and experience.
Good luck with your interviews!