With a career at The Home Depot, you can be yourself and also be part of something bigger.
Position Purpose:
The Lead Data Scientist is responsible for leading data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role assists in the development of the Home Depot advanced analytics infrastructure that informs decision making by applying expertise of both business and Advanced Analytics Modeling techniques. Lead Data Scientists focus on seeking out business opportunities to leverage data science as a competitive advantage. Based on the specific data science team, this role has expertise in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP.
As a Lead Data Scientist, you will be responsible for large data science projects, identifying opportunities to leverage best technology and approach, and mentoring data scientists on the project team. This role is expected to own the library of reusable algorithms for future use, ensuring developed codes are documented. This role supports the building of skilled and talented data science teams by providing input to staffing needs and participating in the recruiting and hiring process. In addition, this role leads data science communities across several business units.
Key Responsibilities:
30% Solution Development - Utilize expertise when designing and developing algorithms and models to use against large datasets to create business insights; Make appropriate selection, utilization and interpretation of advanced analytics methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation
25% Project Management & Team Support - Lead and manage large and complex projects and teams; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team; Serve as a technical subject matter expert (SME) for one or more data science methods, both predictive and prescriptive; Lead data science communities across several business units
20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide technical education on advanced analytics to data science community; Partner with IT to understand potential for new tools and ways to maintain technical agility for data science; Actively seek out new business opportunities to leverage data science as a competitive advantage
25% Technical Exploration & Development - Seek further knowledge on key developments within data science by attending conferences and publishing papers; 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; Define best practices and develop clear vision for data analysis and model productionalization; Ownership of library of reusable algorithms for future use, ensure developed code/models are documented; Develop mastery in one or more prescriptive modeling techniques, like optimization, computer vision, recommendation, search or NLP
Direct Manager/Direct Reports:
This position typically reports to manager or above
This position has 0 Direct Reports and leads/manages projects
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. Demonstrated expertise in Advanced analytic modeling, statistics or BI preferably in retail
Preferred Qualifications:
Masters in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience
10+ 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
Experience in training or mentoring associates is a plus
Experience building agents with Google Gemini ADK or copilot is a plus
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:
10
Preferred Years of Work Experience:
No additional years of experience
Minimum Leadership Experience:
None
Preferred Leadership Experience:
None
Certifications:
None
Competencies:
Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs
Builds Networks: Effectively building formal and informal relationship networks inside and outside the organization
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
Cultivates Innovation: Creating new and better ways for the organization to be successful
Develops Talent: Developing people to meet both their career goals and the organization's goals
Instills Trust: Gaining the confidence and trust of others through honesty, integrity, and authenticity
Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement
Persuades: Using compelling arguments to gain the support and commitment of others
Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels
Strategic Mindset: Seeing ahead to future possibilities and translating them into breakthrough strategies
Tech Savvy: Anticipating and adopting innovations in business building digital and technology applications