Senior Data Scientist - AI Engineer

About the role

The Home Depot's Data Science organization is advancing merchandising decisions through production-grade Agentic AI, MLOps and AIOps. This Senior Data Scientist builds foundational operational frameworks (MLOps, LLMOps, AIOps) and agentic solutions that reason over enterprise data and run core data science models in production workflows. The role combines data science, foundational models, retrieval systems and reusable AI services, and works closely with software engineers and business stakeholders to move solutions from experimentation to production.

Key responsibilities

• Solution development (about 35%): design and develop algorithms and models on large datasets, choose and interpret advanced analytical methods, and communicate insights and recommendations to technical and non-technical leaders
• Project management and team support (about 30%): set project goals with partners, direct prioritization, mentor junior colleagues, help distribute workload and support recruiting
• Business collaboration (about 20%): build trust with internal customers and cross-functional teams, educate them on advanced analytics and look for new business uses of data science
• Technical exploration and development (about 15%): learn new developments, codify data products and best practices, and contribute a library of reusable, documented algorithms

Required profile

• Age 18 or older and legally permitted to work in the United States
• Bachelor's degree or equivalent in a related field
• Preferred: 6+ years of experience in data science, ML engineering, AI engineering, software engineering or MLOps focused on production-ready AI
• Preferred: 2+ years of hands-on experience with GenAI, LLM-based or Agentic AI solutions
• Preferred: domain experience in merchandising, retail, ecommerce, supply chain, assortment planning or space planning

Required skills

• Preferred: Python, SQL, automated testing, Docker/Kubernetes, GCP
• Preferred: MLOps/LLMOps/AIOps practices such as CI/CD, model registries, versioning, monitoring, automated retraining and rollback
• Preferred: AI observability, governance and agent orchestration frameworks, IaC