Lead Data Scientist - Pro

About the role

The Home Depot is looking for a Lead Data Scientist in Pennant Park who leads data science initiatives that drive business profitability, efficiency and customer experience. The role helps build the advanced analytics infrastructure that informs decision making, applies business and advanced analytics modeling expertise, and owns a library of reusable algorithms. It covers large projects, mentoring, staffing input and leading data science communities across business units.

Key responsibilities

• Design and develop algorithms and models for large datasets, choose and interpret advanced analytics methods, and communicate insights to technical and non-technical leaders
• Lead large, complex projects and teams, set priorities, mentor juniors, distribute workload and support recruiting and hiring
• Serve as a technical subject matter expert on predictive and prescriptive methods and lead data science communities across business units
• Build trust with internal customers and cross-functional teams, partner with IT on new tools, and educate the data science community
• Explore developments in data science, publish papers, define best practices and document code and models so they can be reused

Required profile

• Age 18 or older and legally permitted to work in the United States
• Demonstrated expertise in advanced analytic modeling, statistics or BI, preferably in retail
• Bachelor's degree or equivalent in a related field; preferred: master's in a quantitative field or 10+ years of experience in BI, advanced analytics or AI/ML
• Experience designing scalable data pipelines and in predictive modeling, data mining and data analysis
• Experience training or mentoring associates is a plus

Required skills

• Modern scripting language (preferably Python)
• Data querying (SQL/BQ) and visualization (preferably Tableau)
• Statistical techniques to find key insights
• Prescriptive modeling such as optimization, computer vision, recommendation, search or NLP is a plus
• Generative AI: RAG, prompt engineering, LLM orchestration, agent development and evaluation in production is a plus