Sr Data Scientist, Assortment and Space Planning (OR/Optimization)

The Home Depot; Atlanta (GA); On-site; USD 120,000 - 150,000; Full time

Job summary

A leading retail company is seeking a Sr. Data Scientist in Atlanta, Georgia, to develop and deploy scalable mathematical models that enhance business insights and customer experience. Ideal candidates should have a PhD in a quantitative field and substantial experience in optimization model development. The role involves collaboration with various teams, managing projects, and mentoring, making it perfect for someone passionate about advancing data science in a retail setting.

Qualifications

• 6+ years of experience in optimization model development and deployment.
• Strong understanding of data structures and modern cloud ecosystems.
• Proficient in optimization solvers and modern programming languages.

Responsibilities

• Design and develop algorithms and models for business insights.
• Manage projects and mentor junior team members.
• Collaborate with cross-functional teams to identify opportunities.

Skills

Optimization models

Programming in Python

Data visualization (Tableau)

Cloud ecosystems (GCP, AWS)

Collaboration with developers

Education

PhD in a quantitative field

Tools

Gurobi

CPLEX

OR-Tools

Job description

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 optimization 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.

Key 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 reproducible solutions (e.g., 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.

Direct Manager / Direct Report

• This position reports to a manager or above.
• This position has 0 Direct Reports.

Travel Requirements

• Typically requires overnight travel less than 10% of the time.

Physical Requirements

• Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light items.

Working Conditions

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.
• Must be 18 years of age or older. Must be legally permitted to work in the United States.

Preferred Qualifications

• PhD in a quantitative field (Operations Research, Computer Science, AI, Engineering, Applied Math, etc.).
• 6+ years of hands‑on experience developing and deploying optimization 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.
• Proficient in optimization solvers (e.g., Gurobi, CPLEX, OR‑Tools) and modern programming languages (Python, etc.) to prototype and productionize solutions.
• Strong understanding of data structures, and modern cloud ecosystems (GCP, AWS, etc.). Experience leveraging common simulation approaches and/or reinforcement learning techniques.
• Proficient with data visualization software (preferably Tableau). Familiarity with GenAI, LLM and agentic frameworks.
• Comfortable collaborating with front‑end developers or building lightweight UI prototypes (e.g., Streamlit, React).
• Experience solving retail or merchandising problems such as assortment & space optimization, demand transfer, consumer choice models, demand forecasting.

Competencies

• Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs.
• Business Insight: Applying knowledge of the business and the marketplace to advance the organization’s goals.
• Collaborates: Building partnerships and working collaboratively with others to meet shared objectives.
• Communicates Effectively: Developing and delivering multi‑mode communications that convey a clear understanding of the unique needs of different audiences.
• Cultivates Innovation: Creating new and better ways for the organization to be successful.
• Customer Focus: Building strong customer relationships and delivering customer‑centric solutions.
• Develops Talent: Developing people to meet both their career goals and the organization’s goals.
• Directs Work: Provides direction, delegating and removing obstacles to get work done.
• Drives Results: Consistently achieving results, even under tough circumstances.
• Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder.
• Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement.
• Self‑Development: Actively seeking new ways to grow and be challenged using both formal and informal development paths.