Target Data Scientist Interview Questions + Guide in 2024

Target is a major American retail chain known for offering a wide variety of products, including clothing, electronics, groceries, and household essentials. Founded in 1962, Target has grown to become one of the largest discount retailers in the United States.

As a Data Scientist at Target, you play a crucial role in enhancing the company’s operations and customer experience. Data Scientists help Target anticipate consumer behavior, streamline operations, and maintain a competitive edge in the retail market.

In this guide, we’ll share the company’s interview process, provide the commonly asked Target data scientist interview questions, and share some tips to help you successfully prepare for the role.

Target’s data scientist interview process consists of 4 rounds. Here’s what you can expect at each stage:

Recruiter Phone Screen

A short phone call with the recruitment team which consists of sharing your work experience, projects you’ve worked on, and your expectations. This is also an opportunity for you to learn more about the role and company culture, as well as to ask questions that demonstrate your interest and fit for the position.

Technical Rounds

In this round, they will assess your technical knowledge by asking you questions measuring your ability to solve real-world business problems using data-driven insights.

Live Coding

During the session, you’ll be required to demonstrate your problem-solving skills and coding abilities in real-time. Typically, you’ll be given a specific problem or task, and you’ll need to write and debug code while explaining your thought process to the interviewer.

Behavioral Rounds

This final round is important to determine whether if you’ll be a good fit to the team and how well you align with the company’s values and work environment. The focus on this round is on assessing your soft skills, such as communication, teamwork, problem-solving, and adaptability.

Here are a few questions that get asked in Target data scientist interviews:

1. Why do you want to work at Target?
2. How do you avoid overfitting?
3. Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender.
4. Write a query to identify customers who placed more than three transactions each in both 2019 and 2020.
5. Write a function to return a dataframe containing every transaction with a total value of over $100. Include the total value of the transaction as a new column in the dataframe.
6. How would you forecast revenue for the next year?
7. You conducted an A/B test mentioning free shipping on the checkout page. How would you evaluate the results and if the test was successful or not?
8. What are the benefits of dynamic pricing, and how can you estimate supply and demand in this context?
9. In a city, the probability that item X is at warehouse A is 0.6 and at warehouse B is 0.8. If item X is listed on Amazon’s website only if it’s at one of these warehouses, what’s the probability it will be found on the website?
10. Given a table of transactions and a table of users, write a query to determine if users tend to order more to their primary address versus other addresses.
11. Given a dataset, how would you analyze the dataset to understand exactly where the revenue loss is occurring?
12. Let’s say we have a sample size of n. The margin of error for our sample size is 3. How many more samples would we need to decrease the margin of error to 0.3?
13. How would you explain what a p-value is to someone who is not technical?
14. How would you get rid of duplicate products that may be listed under different names, etc.. in a very large database?
15. Find a user that has the highest average number of unique item categories per order.
16. You have access to historical prices data from products that have been on sale before. How would you determine what products should go on sale to best maximize profit during Black Friday?
17. How would you determine the customer service quality through the chat box for all interactions involving small businesses selling items to consumers?
18. Describe a data project you worked on. What were some of the challenges you faced?
19. Tell me about a project in which you had to clean and organize a large dataset.
20. How do you prioritize multiple deadlines?

Understand the Role and Company

Research Target’s business model, data initiatives, and industry challenges. Familiarize yourself with how Target uses data science to drive decisions and improve operations.

Brush Up Your Technical Skills

Practice your technical skills in machine learning, statistics, and SQL, as these are crucial for the role. Also prepare for case study questions where you’ll analyze data and make recommendations.

Don’t Forget to Practice Behavioral Interview Questions

Be ready to discuss your past experiences using the STAR (Situation, Task, Action, Result) method. Prepare to talk about teamwork, problem-solving, and how you handle challenges as these are common on behavioral interviews.

Conduct Mock Interviews with Peers

Practice with mock interviews or our AI interviewer to refine your responses and get feedback. This will help you articulate your skills and experiences clearly and confidently during the actual interview.

What is the average salary for a data scientist role at Target?

The average base salary for a Data Scientist at Target is $136,501, with the highest earners earning at $190k/yr

What other companies are hiring Data Scientists besides Target?

Numerous companies are hiring Data Scientists across various industries. Some well-known examples include Google, JPMorgan Chase, and Amazon

Does Interview Query have job postings for Target Data Science roles?

Yes, visit our Job Board to check out current opportunities.

While the Target data scientist interview process can be technically demanding for the candidates, we hope this Target interview guide provides valuable support. Best of luck on your journey!