About this opportunity
Home Depot / THD lists this Sr Data Scientist - AI Engineer opportunity in atlanta, Georgia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Home Depot’s THD data science team is looking for a Senior Data Scientist to build production-ready AI capabilities that connect enterprise data to real workflows. This role focuses on establishing MLOps/LLMOps/AIOps operational frameworks and developing agentic AI solutions that can reason over data and orchestrate models into end-to-end execution.
What you will do
You will take ownership of solution development across advanced analytics, from designing models for large datasets to selecting and applying analytical methodologies that support business outcomes. A major part of the work includes ensuring outputs are executed with strong efficiency and quality, then translating results into clear recommendations for technical and non-technical leaders.
Design and develop algorithms and models that generate business insights from large datasets
Apply advanced analytical methodologies, including appropriate selection, utilization, and interpretation
Communicate insights and recommendation impacts to drive alignment and implementation
Prepare reports, updates, and presentations on progress for projects and solutions
You will also collaborate across teams to shape project direction and execution. This includes helping set goals, guiding prioritization, and supporting team quality through direction and coaching of more junior roles. The role includes coordination with managers and teams on workload and resource distribution, and involvement in recruiting and hiring efforts for the group.
Work with project teams and business partners to determine project goals
Provide direction on prioritization and ensure quality of work
Mentor and coach more junior roles to strengthen technical competencies
Collaborate with managers and teams on distribution of workload and resources
Support recruiting and hiring efforts for the team
Additional responsibilities include leveraging business context to improve solution approaches and building trusted relationships with internal customers and cross-functional teams. You will also support partner enablement by providing general education on advanced analytics, aligned with your understanding of IT needs required to solve business problems and create data science advantage.
Leverage business knowledge to shape the solution approach
Develop trust and collaboration with internal customers and cross-functional teams
Educate technical and non-technical partners on advanced analytics
Apply a deep understanding of IT needs to help the team tackle business problems
Actively pursue new business opportunities where data science can drive competitive advantage
On the technical side, you will continue exploring emerging capabilities and improving how solutions are delivered. This includes developing replicable, well-documented solutions (such as codified data products, project documentation, and process flowcharts), defining best practices for data analysis and model productionalization, and contributing to a reusable library of algorithms with clear documentation.
Stay current on key data science developments, technical skill sets, and additional data sources
Improve data science and analytics through replicable solutions for future reuse
Define best practices and develop a clear vision for productionalization
Contribute to a library of reusable algorithms with documented code
Requirements
Must be eighteen years of age or older
Must be legally permitted to work in the United States
Minimum 6+ years of experience in data science, machine learning engineering, AI engineering, software engineering, or MLOps, focused on production-ready AI solutions
2+ years of hands‑on experience developing, deploying, evaluating, or supporting GenAI, LLM‑based, or agentic AI solutions
Experience building agentic AI systems and multi‑step workflows using tool calling, reasoning and planning, state and memory management, structured outputs, RAG/retrieval systems, embeddings, and API integration
Strong software engineering skills: Python, SQL, automated testing, containerization (Docker/Kubernetes), and cloud deployment (GCP preferred), with collaboration across Engineering, DevOps, and SRE partners
Expertise in foundational MLOps/LLMOps/AIOps practices: CI/CD automation, model/agent registries, versioning, automated testing, monitoring, automated retraining, rollback strategies, release management, and production support
Expertise in AI observability and governance: tracing, telemetry, automated alerting, anomaly detection, incident triage, eval harnesses, safety guardrails, model explainability, approval paths, fallback mechanisms, tool‑use auditing, and cost/latency monitoring, including human‑in‑the‑loop controls
Hands‑on experience with agent orchestration frameworks, structured agent communication protocols (MCP, A2A), and Infrastructure‑as‑Code (IaC)
Ability to prototype lightweight tools or interfaces, evaluate technical feasibility, and document reusable architectural patterns
Continuous learning agility for emerging AI architectures, protocols, and operating models
Domain experience in merchandising, retail, ecommerce, supply chain, assortment planning, or space planning
Tools and technologies
Python, SQL
Docker, Kubernetes
GCP
CI/CD, CI/CD automation
RAG, retrieval systems, embeddings
API integration
MLOps, LLMOps, AIOps
IaC, MCP, A2A
Role details
Location: Atlanta, GA (onsite)
Minimum years of work experience: 5
Travel: typically requires overnight travel less than 10% of the time
Education: bachelor’s degree program or equivalent degree in a field of study related to the job
Reporting: this position reports to manager or above; 0 direct reports
Working conditions
Most of the time is spent sitting in a comfortable position, with frequent opportunity to move about
On rare occasions, there may be a need to move or lift light articles
Located in a comfortable indoor area; any unpleasant conditions would be infrequent and not objectionable
Competencies
Attracts Top Talent
Business Insight
Collaborates
Communicates Effectively
Cultivates Innovation
Customer Focus
Develops Talent
Directs Work
Drives Results
Nimble Learning
Optimizes Work Processes
Self-Development
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Worksite address
atlanta, GA, 30383, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.