With a career at The Home Depot, you can be yourself and also be part of something bigger.
Position Purpose:
The Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies, and improved candidate/associate experiences. This role applies industry-leading analytical methodologies and cutting-edge artificial intelligence for working with large, complex HR datasets to extract meaningful business insight and creatively solve business problems. Data Scientists are also responsible for ensuring that developed code is documented and maintained using modern version control (e.g., GitHub) as a library of reusable algorithms. This role requires deep knowledge in specialized data science areas, particularly in recommendation systems, Natural Language Processing (NLP), Generative AI, and agentic workflows.
As a Data Scientist, you will apply advanced analytics methods, machine learning algorithms, and Large Language Models (LLMs) to identify trends and provide highly scalable business solutions. You will be expected to own the end-to-end MLOps lifecycle—from ideation and research to deploying models into active production environments. This role must present complex insights and recommendations to non-technical audiences, explaining the benefits and impacts of the proposed solutions. In addition, Data Scientists collaborate tightly with IT, Staffing, and cross-functional business partners, requiring effective communication skills, relationship building, and a strong focus on understanding the overarching People Analytics ecosystem.
Key Responsibilities:
- 55% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies
- 20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Present recommendations in a confident manner in order to influence execution of recommendation; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation
- 10% Business Collaboration - Incorporate business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Work with project teams and business partners to determine project goals
- 15% Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented
Direct Manager/Direct Reports:
- This position typically reports to Manager or above
- This position has 0 Direct Reports
Travel Requirements:
- Typically requires overnight travel less than 10% of the time.
Physical Requirements:
- Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.
Working Conditions:
- Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
Minimum Qualifications:
- Must be eighteen years of age or older.
- Must be legally permitted to work in the United States.
Preferred Qualifications:
- Masters in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience
- 4+ years of experience in data science, advanced analytics, and building production-level ML systems
- Working knowledge of Microsoft Excel and Power Point
- Proficient in Python (including Pandas and NumPy) and version control utilizing Git/GitHub
- Proficient running queries against large-scale databases (preferably with Google BigQuery, SQL, and GCP)
- Proficient with data visualization software (preferably Tableau)
- Proficient with the end-to-end MLOps lifecycle, model deployment, and API serving (preferably with Kubeflow or MLflow)
- Knowledgeable in Generative AI, LLM-powered agentic workflows, and recommendation systems
Minimum Education:
- The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.
Preferred Education:
Minimum Years of Work Experience:
Preferred Years of Work Experience:
- No additional years of experience
Minimum Leadership Experience:
Preferred Leadership Experience:
Certifications:
Competencies:
- Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm
- Business Insight: Applying knowledge of the business and the marketplace to advance the organization's goals
- Collaborates: Building partnerships and working collaboratively with others to meet shared objectives
- Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences
- Customer Focus: Building strong customer relationships and delivering customer-centric solutions
- Drives Results: Consistently achieving results, even under tough circumstances
- Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder
- Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement
- Plans and Aligns: Planning and prioritizing work to meet commitments aligned with organizational goals
- Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels
