Lead Data Scientist, Assortment and Space Planning; AI-Engineering

Position: Lead Data Scientist, Assortment and Space Planning (AI-Engineering)

Lead Data Scientist, Assortment and Space Planning (AI-Engineering)

Join to apply for the Lead Data Scientist, Assortment and Space Planning (AI-Engineering) role at The Home Depot

Position Purpose

We are transforming how merchandising decisions are made through AI-powered solutions and automation. This Lead Data Scientist plays a key role in designing and building state-of-the-art GenAI and Agentic AI Systems that enable autonomous decision recommendations. The position focuses on orchestrating LLMs with existing foundational models to deliver adaptive, learning decision systems that increase efficiency and improve customer experience.

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 (e.g., 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;
  Own 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.

Minimum Qualifications

• Demonstrated expertise in predictive modeling, data mining and data analysis.
• Demonstrated expertise utilizing statistical techniques to identify key insights that help solve business problems.
• Must be 18 years of age or older.
• Must be legally permitted to work in the United States.

Preferred Qualifications

• 10+ years of combined AI engineering experience or equivalent in software engineering or ML engineering.
• 2+ years of experience developing/deploying GenAI or LLM-driven automated systems, and Agentic AI evaluation frameworks at scale.
• Hands‑on experience with LLM agent orchestration frameworks (Lang Graph, Lang Chain etc.).
• Strong understanding of structured agent interactions (e.g., MCP and A2A).
• Proven experience deploying models and APIs in containerized, cloud‑neutral environments.
• Proficiency in prompt engineering, RAG implementation, and LLM fine tuning.
• Familiarity with agentic IDEs (e.g., Git Hub Copilot, Cursor, etc.).
• Experience with GCP cloud computing platform.
• Practical knowledge of vector databases and exposure to knowledge graphs (e.g., Neo4j), embeddings, or multimodal data ingestion.
• Comfortable collaborating with front‑end developers or building light UI prototypes (e.g., Streamlit, React).
• Contributions to open‑source AI/ML tooling or orchestration frameworks.
• Domain experience in merchandising, retail, e‑commerce, or supply chain.

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 years.

Preferred Years Of Work Experience

No additional years of experience.

Minimum Leadership Experience

None.

Preferred Leadership Experience

None.

Certifications

None.

Competencies

Attracts Top Talent;
Builds Networks;
Business Insight;
Collaborates;
Communicates Effectively;
Cultivates Innovation;
Develops Talent;
Instills Trust;
Optimizes Work Processes;
Persuades;
Self‑Development;
Strategic Mindset;
Tech Savvy.

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