Dollar General, a leading retail chain in the United States, is recognized for its widespread reach and affordability in offering everyday essentials. With thousands of stores across the nation, Dollar General maintains a significant presence in the retail industry. The company is currently seeking talented Machine Learning Engineers to join its innovative tech team.

The Machine Learning Engineer position at Dollar General involves working on cutting-edge projects that drive the company's data strategy and enhance customer experiences. Candidates are expected to have strong technical skills in machine learning algorithms, data processing, and software development. This role also requires proficiency in Python, TensorFlow, and other relevant tools.

At Interview Query, we aim to provide you with an in-depth understanding of the interview process for this position. This guide will shed light on what to expect, key questions, and useful tips for securing a role as a Machine Learning Engineer at Dollar General. Let's dive in!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Dollar General as a Machine Learning Engineer. Whether you were contacted by a Dollar General recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Dollar General Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Dollar General Machine Learning Engineer hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Dollar General Machine Learning Engineer role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Dollar General’s data systems, machine learning algorithms, and coding challenges.

In the case of machine learning roles, take-home assignments regarding algorithm design, data modeling, and model evaluation are incorporated. Apart from these, your proficiency against hypothesis testing, probability distributions, and machine learning fundamentals may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Dollar General office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Machine Learning Engineer role at Dollar General.

Quick Tips For Dollar General Machine Learning Engineer Interviews

• Understand Retail Data: Dollar General heavily relies on data related to retail and inventory. Brush up on common retail metrics and data analysis techniques.
• Showcase Real-World Problem-Solving: Highlight how you’ve used machine learning to solve real-world problems in your past experiences. Give specific examples.
• Cultural Fit: Dollar General values a collaborative work environment. Practice responding to behavioral questions that demonstrate your ability to work well in teams and align with the company’s values.

Typically, interviews at Dollar General vary by role and team, but commonly Machine Learning Engineer interviews follow a fairly standardized process across these question topics.

• Create a function recurring_char to find the first recurring character in a string. Given a string, write a function recurring_char to find its first recurring character. Return None if there is no recurring character. Treat upper and lower case letters as distinct characters. Assume the input string includes no spaces.

• Write a query to get the average order value by gender. Given three tables representing customer transactions and customer attributes, write a query to get the average order value by gender. Round your answer to two decimal places.

• Identify first-time and repeat purchases within product categories. Analyze a user's purchases to identify which purchases represent the first time the user has bought a product from its category and which represent repeat purchases. Output a table including every purchase with a boolean column indicating if it’s a repeat purchase.

• Parse the most frequent words used in poems. Given a list of strings called sentences, return a dictionary of the frequency that words are used in the poem. Process all words as lowercase and ignore punctuation marks.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, select the next highest salary.

• How would you address a 10% decline in friend requests on Facebook? A product manager at Facebook reports a 10% decrease in friend requests. What steps would you take to investigate and address this issue?

• How would you set up an A/B test for button color and position in a sign-up funnel? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What metrics would you use to evaluate the value of marketing channels for Mode? Given all the different marketing channels and their respective costs for Mode, a company selling B2B analytics dashboards, what metrics would you use to determine the value of each marketing channel?

• How would you measure the success of a banner ad strategy for an online media company? An online media company wants to experiment with adding web banners into the middle of its reading content to monetize effectively. How would you measure the success of this banner ad strategy?

• How would you investigate a drop in Facebook post activity from 3% to 2.5% per user? Facebook's posting tool usage dropped from 3% posts per user last month to 2.5% today. How would you investigate this decline? If the drop is in photo posts, what specific aspects would you investigate?

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• What is the difference between covariance and correlation? Provide an example. Describe the difference between covariance and correlation, and provide an example to illustrate the distinction.

• What are time series models? Why do we need them when we have less complicated regression models? Explain what time series models are and why they are necessary despite the availability of simpler regression models.

• How would you determine if the difference between this month and the previous month in a time series dataset is significant? Given a time series dataset grouped monthly for the past five years, describe how you would assess if the difference between this month and the previous month is significant.

• How would you address a manager's complaint about a packet filling machine not functioning correctly? A manager reports that a machine, which weighs and attempts to pack 25 packets into a box, is malfunctioning. Customers are complaining about incorrect packet counts. How would you investigate and resolve this issue?

• How does random forest generate the forest and why use it over logistic regression? Explain the process of generating a forest in random forest and discuss the advantages of using random forest over logistic regression.

• How would you justify using a neural network model and explain its predictions to non-technical stakeholders? Describe how you would justify the complexity of a neural network model for solving a business problem and how you would explain its predictions to non-technical stakeholders.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain the interpretation of logistic regression coefficients for categorical and boolean variables.

• Which model would perform better for predicting Airbnb booking prices: linear regression or random forest regression? Compare the performance of linear regression and random forest regression for predicting booking prices on Airbnb and explain which model would likely perform better and why.

• What are the assumptions of linear regression? List and explain the key assumptions underlying linear regression.

If you want more insights about the company, check out our main Dollar General Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Dollar General’s interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Dollar General machine learning engineer interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!