Sr Data Scientist- Assortment and Space Planning (Core ML)

The Home Depot • Atlanta, GA

3d

About The Position

With a career at The Home Depot, you can be yourself and also be part of something bigger. Position Purpose: We are transforming how merchandising decisions are made through AI-powered solutions and automation. This Sr. Data Scientist plays a key role to build scalable, mathematical algorithms in production that directly impact retail and merchandising by solving complex, high-value business problems. The position focuses on science-driven models, operating at the intersection of data science, process automation, cloud deployment, and software production to deliver reliable decision systems that increase efficiency and improve customer experience. This role leads Machine Learning initiatives end-to-end, from cross-functional collaboration and business problem framing through technical design, development, deployment, and ongoing monitoring and enhancement. The Sr. Data Scientist partners closely with product managers, software engineers, and business stakeholders to identify high-impact opportunities, translate into technical requirements, and deliver scalable solutions in production. The role is responsible for communicating insights and recommendations to both technical and non-technical audiences, mentoring data scientists on projects, and ensuring models perform effectively based on real-world outcomes.

Requirements

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.
• 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.

Nice To Haves

• Master’s or PhD in Data Science, Statistics, Economics, Applied Math, Engineering, or other quantitative and engineering fields.
• 6+ years of hands-on experience developing and deploying Machine Learning models into production environments and integrating into scalable data pipelines and decision systems (e.g., via APIs, microservices, or batch pipelines), ensuring reliability, scalability, traceability, and interoperability.
• Deep expertise in causal inference (e.g., Difference-in-Differences, Double ML, Synthetic Control) and discrete choice models, including elasticity, substitution and demand transfer.
• Solid foundation in machine learning models (e.g., regularized regression, tree-based methods such as XGBoost, and neural networks)
• Strong experience with forecasting models (e.g., time-series forecasting. ARIMA, Bayesian and probabilistic methods or deep learning-based approaches).
• Strong understanding of data structures, and modern cloud ecosystems (GCP, AWS, etc.).
• Proficient with data visualization software (preferably Tableau).
• Familiarity with GenAI, LLM and Agentic framework, with experience integrating LLM-based reasoning into ML-driven solutions.
• Comfortable collaborating with front-end developers or building light UI prototypes (e.g., Streamlit, React).
• Demonstrated strength in business communication and technical leadership, with the ability to clearly explain complex statistical and ML concepts to non-technical stakeholders in a way that builds trust and drives adoption.
• Experience solving retail or merchandising problems such as assortment & space optimization, demand transfer, consumer choice models, demand forecasting.

Responsibilities

• Solution Development - Proficiently design and develop algorithms and models to use against large datasets to create business insights; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation
• Project Management & Team Support - Work with project teams and business partners to determine project goals; 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
• Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide general education on advanced analytics to technical and non-technical business partners; Deep understanding of IT needs for the team to be successful in tackling business problems; Actively seek out new business opportunities to leverage data science as a competitive advantage
• Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, 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; Contribute to library of reusable algorithms for future use, ensuring developed codes are documented

What This Job Offers

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