Data Scientist

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 customer experience. This role applies industry-leading analytical methodologies for working with large datasets to extract meaningful business insight and creatively solve business problems. Data Scientists are also responsible for ensuring that developed codes are documented into a library of reusable algorithms. Based on the specific data science team, this role would need to be knowledgeable in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP.

As a Data Scientist, you will apply advanced analytics methods and algorithms for identifying trends and providing business solutions. This role is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships, and focus on understanding the overall business area being supported.

This role is based on‑site and requires full‑time, five‑day‑a‑week presence in the office.

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 business intelligence, advanced analytics, and/or AI/ML fields.

• Experience designing, building, and maintaining scalable data pipelines to support ingestion, processing, and transformation from multiple sources (e.g., databases, APIs, streaming).

• Experience in a modern scripting language (preferably Python)

• Proficient in Data querying (SQL/BQ) and visualization (preferably tableau)

• Proficient utilizing statistical techniques to identify key insights that help solve business problems

• Knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search, or traditional NLP is a plus.

• Familiarity or hands-on experience in designing, developing, and deploying autonomous AI agents or multi-agent systems using modern LLM orchestration frameworks.

• Experience with Retrieval-Augmented Generation (RAG) architectures, prompt engineering, and enabling LLMs with tool/function calling capabilities to interact with external APIs and databases.

• Understanding of evaluating, testing, and monitoring generative AI models and agents in production environments to ensure reliability, safety, and performance.

• Demonstrated experience in predictive modeling, data mining and data analysis

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:

• No additional education

Minimum Years of Work Experience:

• 3

Preferred Years of Work Experience:

• No additional years of experience

Minimum Leadership Experience:

• None

Preferred Leadership Experience:

• None

Certifications:

• None

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