Jobs

Data Science PhD Level Internship (Summer 2026 - Hybrid/In-Office)
STORE SUPPORT CENTER, ATLANTA - 9090
·
On-site
·
Internship
·
1w ago
Compensation
$50,000 - $50,000
Benefits & Perks
•Housing assistance
Required Skills
Data analytics
Python
SQL
With a career at The Home Depot, you can be yourself and also be part of something bigger.
- Internship format will be 4 days a week in office (Monday
- Thursday & Friday's Remote)
Internship Overview
The Home Depot’s Summer Internship program offers college students an opportunity to develop leadership skills and gain hands on experience in a corporate environment. During an 11 – week period from May 18 - July 31, 2026, interns will be assigned to a functional team such as Supply Chain, Marketing, e-commerce, Technology, Finance, Operations, Merchandising, Pro, Home Services, Human Resources, etc. Interns will learn more about our retail business and our corporate offices while having the opportunity to work on a pre-assigned project that impacts the function they are supporting. Additionally, interns participate in networking and development activities that set them up for success as they build their careers.
What makes a Great Intern:
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Action Oriented: Intern takes on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm
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Manages Ambiguity: Intern effectively navigates and thrives in uncertain situations while using sound judgment to make decisions without having the full picture. Is able to move work forward without all the details
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Collaboration: Intern contributes to the group’s efforts and steps forward to help as needed. Seeks input from others
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Nimble Learning: Intern actively learns through experimentation when tackling new problems, using both successes and failures as learning fodder
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Communication: Intern develops and delivers multi-mode communications that convey a clear understanding of the unique needs of different audience
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Customer Focus: Intern builds strong customer relationships and delivers customer-centric solutions
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Drives Results: Evaluates information to make logical decisions and achieve results despite potential challenges or setbacks.
Description of the major/subject area
The Data Science Intern Program offers talented students pursuing a PhD in Data Science the opportunity to develop their advanced data science skills while supporting the Company’s strategic objectives. Intern candidates are assigned to a project aligned to business areas such as e-Commerce, Merchandising, Operations or Finance. The Home Depot’s internship program was recently named in the Top 20 in the US and offers college students an opportunity to develop leadership skills and gain hands on experience working with a number of leaders on projects that directly impact the business for one of the world's leading retailers. Data Science interns will focus on working with a variety of data science roles and functions to translate business questions into actionable insights and deliver high quality analytical solutions.
Tasks, responsibilities, and key accountabilities include:
Business Collaboration
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Participate in meetings across the enterprise data science community, gaining exposure to cross functional business units.
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Build networking relationships and receive mentoring from team members and top-level management
Communicating Results
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Communicate findings and project status clearly and professionally through presentations
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Provide recommendations to upper management.
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Provide comprehensive report-out to senior leaders on assignments and other related projects
Data Analytics
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Use strategic thinking and perform data analytics for a variety of business problems and opportunities and create high quality analytics solutions
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Apply a wide variety of database applications and analytical tools, including SQL, Google Cloud Big Query and Python
Preferred Qualifications
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Working knowledge of Microsoft Office Suite
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Working knowledge of Tableau
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Working knowledge of presentation software (e.g., Microsoft PowerPoint)
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Currently pursuing a PhD degree in a quantitative field (Analytics, Finance, Information Systems, etc.)
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Excellent academic performance
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Experience in a modern scripting language (preferably Python)
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Experience running queries against data (preferably with Google Big Query or SQL)
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Experience with data visualization software (preferably Tableau)
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Exposure to statistics, predictive modeling and other data science methodologies
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Preferred GPA 3.0 or above
Description of Roles: (Career paths that utilize this skillset full-time)
At The Home Depot, our associates always have room to move up and explore new opportunities. After the Internship, here are some examples of early career roles for interns with a background in Data Science:
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Data Science Analyst
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Associate Data Scientist
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Data Scientist
Location: Interns will be expected to work in-person at the Atlanta Corporate Office (Store Support Center) four days a week (Monday-Thursday) and will work remotely one day a week (Fridays) during the 11-week program. Housing assistance will be provided to eligible interns.
For California, Colorado, Connecticut, Rhode Island, Nevada, New York City, Ithaca (NY), Westchester County (NY), and Washington residents:
The pay range for this position is between $50 - $50
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About The Home Depot
Reviews
3.9
2 reviews
Work Life Balance
3.0
Compensation
2.5
Culture
3.0
Career
2.0
Management
3.5
35%
Recommend to a Friend
Pros
Strong job performance and recognition
Management support and recommendations
Opportunity to manage specialty departments
Cons
Limited path from contract to permanent employee
Contract employment instability
State tax complications affecting hiring
Salary Ranges
2 data points
Junior/L3
Junior/L3 · Customer Service
1 reports
-
total / year
Base
$16
Stock
-
Bonus
-
Interview Experience
6 interviews
Difficulty
2.0
/ 5
Duration
21-35 weeks
Offer Rate
33%
Experience
Positive 33%
Neutral 17%
Negative 50%
Interview Process
1
Application Review
2
Online Assessment/Screen
3
HR Screen
4
Hiring Manager Interview
5
Technical Assessment
6
Offer
Common Questions
Behavioral/STAR
Customer Service Scenarios
Technical Knowledge
Past Experience
Culture Fit
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