Sr. Product Manager

The Home Depot•Atlanta, GA

About The Position

The Sr. Product Manager drives the strategy, development, and scaling of enterprise AI/ML and data-driven products that enable actionable insights and support business decision-making. The role defines product vision and roadmaps for advanced analytics and AI platforms, translating complex business problems into scalable solutions. It partners with engineering and data science teams to design products using machine learning models, generative AI, and large-scale data systems, and oversees intelligent features such as automated insights, reporting systems, and decision-support tools built from structured and unstructured data. The position manages product lifecycles in a technical environment, including backlog creation, prioritization, and delivery of features involving data pipelines, models, and platform components. It balances business impact with technical feasibility and platform extensibility, communicates technical concepts as clear product requirements, and works across Engineering, Data Science, UX, and Analytics to deliver and continuously improve production-ready solutions. The role also assesses market trends and emerging AI/ML and analytics technologies, establishes standards for data-driven products and reporting solutions, and guides best practices in technical product management and execution.

Requirements

Must be at least 18 years of age.
Must be legally permitted to work in the United States.
Bachelor’s degree in Computer Science, Information Technology, Analytics, Business Administration, or a related field.
Three years of experience in a related occupation, including three years of experience in the listed skills.
Product management experience in enterprise AI/ML, automation, and data platform environments.
Experience translating business requirements into machine learning or advanced analytics solutions.
Experience developing, evaluating, and deploying models in production environments with data science teams.
Experience with cloud-based data and analytics platforms, such as SQL, IBM Cloud, or similar technologies.
Experience managing products built on large-scale structured and unstructured datasets.
Experience building or scaling data-driven products, analytics platforms, or reporting systems.
Experience developing AI-powered insights, dashboards, or decision-support tools.
Experience working in modern Agile software development environments for data and AI products.
Experience creating and managing complex product backlogs involving data pipelines, models, and platform components.
Experience conducting user research and translating findings into product requirements and technical specifications.
Experience working with cross-functional Engineering, Data Science, UX, and Analytics teams.
Experience conducting competitive analysis in AI/ML, data, or analytics product domains.

Responsibilities

Drive the strategy, development, and scaling of enterprise AI/ML and data-driven products that enable actionable insights and business decision-making.
Define product vision and roadmaps for advanced analytics and AI platforms, translating complex business problems into scalable, data-driven solutions.
Partner with engineering and data science teams to design products using machine learning models, generative AI capabilities, and large-scale data systems.
Oversee development of intelligent features, including automated insights, reporting systems, and decision-support tools built on structured and unstructured data.
Ensure solutions are scalable, reliable, and integrated within enterprise data ecosystems.
Manage technical product lifecycles, including backlog creation, prioritization, and delivery of features involving data pipelines, models, and platform components.
Balance business impact with technical feasibility and platform extensibility in product decisions.
Translate technical concepts into product requirements and stakeholder communications to align technical and non-technical teams.
Collaborate with Engineering, Data Science, UX, and Analytics to deliver production-ready solutions and improve product capabilities.
Assess AI/ML and analytics market trends and emerging technologies to inform product direction and maintain competitive positioning.
Establish standards for data-driven products and reporting solutions to promote consistency, scalability, and long-term usability.
Guide team development by supporting best practices in technical product management and execution.