Data Scientist

The Home Depot

5d • Onsite

About The Position

With a career at The Home Depot, you can be yourself and also be part of something bigger. Job Description Title: Data Scientist Position Overview: The Data Scientist is a key member of the Advanced Analytics team, responsible for developing and deploying advanced statistical and machine‑learning models that support high‑impact business decisions. This role focuses on transforming large‑scale, complex datasets into predictive insights that improve demand forecasting, inventory decisions, pricing strategies, and overall retail performance.

Requirements

• Advanced analytical and quantitative reasoning
• Business partnership and communication
• Statistical modeling and machine‑learning techniques
• Data storytelling and insight translation
• Master’s degree or Ph.D. in Data Science, Statistics, Operations Research, Economics, Computer Science, or a related quantitative field Equivalent practical experience may be considered
• 3+ years of professional experience in data science, analytics, or statistical modeling
• Not required Minimum Leadership Experience
• Strong proficiency in Python and SQL, with experience using common data science libraries (e.g., Pandas, Scikit‑learn, TensorFlow, PyTorch)
• Experience working with cloud platforms, preferably Google Cloud Platform (BigQuery, Vertex AI, Cloud Storage)
• Expertise in time‑series forecasting and statistical modeling techniques
• Experience with optimization methods and algorithms
• Knowledge of retail analytics, including demand forecasting, pricing, inventory, and promotions
• Familiarity with A/B testing, experimental design, and causal inference methodologies
• Ability to communicate complex technical findings to non‑technical stakeholders

Responsibilities

• Predictive Modeling & Advanced Analytics Design, build, optimize, and maintain scalable, production‑ready forecasting and machine‑learning models.
• Develop time‑series models to predict customer demand at multiple levels of granularity.
• Design and execute “what‑if” scenarios to assess the impact of changes in pricing, promotions, and inventory on demand and profitability.
• Data Preparation & Feature Engineering Identify, clean, and engineer features such as seasonality, trends, promotional uplift, cannibalization effects, competitor activity, and macroeconomic drivers.
• Analyze and synthesize large‑scale datasets from multiple internal and external sources to support modeling efforts.
• Collaboration, Deployment & Monitoring Partner with business stakeholders to translate business questions into analytical solutions.
• Collaborate with Data Engineering to ensure access to reliable, scalable data pipelines.
• Work with MLOps teams to support model deployment, performance monitoring, and ongoing recalibration as data or business conditions evolve.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level