Data Scientist

Innovate in Charlotte Thank you for dedicating your time and talent to Lowe’s. We want to give you more opportunities to learn and grow, so if you find a position you’re interested in below, we encourage you to apply! Your Impact Join Lowe’s Data, Analytics & Customer Insights organization and apply data science to business problems that directly influence how Lowe’s forecasts demand, plans inventory, and makes pricing and promotion decisions. In this role, you’ll support data science initiatives across Merchandising and Supply Chain Intelligence, including Pricing & Promotion Analytics and the Lowe’s Forecasting Platform. You’ll partner with Product, Engineering, Analytics, and Business teams to build, validate, and translate models and insights that support demand forecasting, pricing decisions, measurement, inventory planning, and merchant-facing technology products. This is an opportunity to work at the intersection of data science, retail decision-making, and technology, turning complex data into scalable solutions and actionable recommendations. What You’ll Do • Build models that influence forecasting, pricing, promotions, and supply chain decisions. Develop and improve predictive models, forecasting engines, and machine learning capabilities supporting the Lowe’s Forecasting Platform and key merchandising retail strategies. • Turn complex pricing questions into measurable insights. Apply statistical modeling, causal inference, and experimentation to demand modeling, price recommendations, measurement, halo/cannibalization, and test-and-learn initiatives. • Work with large-scale retail data. Use SQL, Python, Spark/PySpark, and cloud platforms to prepare reusable datasets, validation checks, and model-ready features. • Translate business challenges into data science solutions. Partner with Product, Engineering, Analytics, and Business teams to define model requirements, success metrics, and production-ready approaches. • Help ensure models deliver measurable business value. Evaluate model performance, forecast variance, assumptions, limitations, explainability, and adoption risks. • Make complex findings actionable. Communicate recommendations to technical and non-technical audiences through dashboards, validation summaries, documentation, and decision-support materials. What You Bring: • Bachelor’s degree in mathematics, statistics, physics, economics, engineering, computer science, data, information science, or related quantitative analytic field, or equivalent years of experience in lieu of education requirement, if applicable. • 2 years of experience executing and deploying data science, machine learning, deep learning, and generative AI solutions, preferably in a large-scale enterprise setting. Fewer years may be accepted with a master’s or doctorate degree. • 1 year of SQL and programming experience. Fewer years may be accepted with a master’s or doctorate degree. It's a plus if you have: We encourage you to apply even if you do not have all the preferred skills or experience. • 2 years of experience with forecasting, demand planning, pricing, promotions, merchandising, retail, or supply chain analytics. • 2 years of experience with statistical modeling, causal inference, experimentation, predictive analytics, or prescriptive analytics in a large-scale enterprise environment. • 2 years of experience using SQL, Python, Spark/PySpark, cloud platforms, or ML workflow tools such as GCP, Vertex AI, MLflow, AWS, or Azure. • Experience partnering with cross-functional teams and translating model outputs into business recommendations, documentation, validation artifacts, or production requirements. Why Join Us? • Impactful Work: Shape the future of Order Management by building critical services that directly impact customer experience. • Growth Opportunities: Continuous learning with the latest tech trends and opportunities to explore new tools and frameworks. • Collaborative Environment: Work…