The Home Depot

Sr. Product Manager

The Home Depot Atlanta, Georgia, United States

Retail · 10,001+ employees

2 d ago
product-manager Mid (2-5 yrs) Full-time United States
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About the role

The Sr. Product Manager will drive the strategy, development, and scaling of enterprise AI/ML and data-driven products. They will collaborate with engineering and data science teams to translate complex business problems into scalable, production-ready solutions.

What they look for

Product Management Artificial Intelligence Machine Learning Data Analytics Data Platforms Generative AI SQL Agile Methodology Product Roadmap Data Pipelines Decision Support Tools Cross-functional Collaboration User Research Competitive Analysis Technical Requirements Enterprise Systems

Requirements

Candidates must have a bachelor's degree in a relevant field and at least 3 years of experience in enterprise AI/ML and data platform environments. Proficiency in managing product lifecycles, working with cloud-based data platforms, and translating technical requirements is required.

Full description

With a career at The Home Depot, you can be yourself and also be part of something bigger.

Key Responsibilities:

  • Responsible for driving the strategy, development, and scaling of enterprise AI/ML and data-driven products that enable actionable insights and support business decision-making.
  • Define product vision and roadmap for advanced analytics and AI platforms by translating complex business problems into scalable, data-driven solutions.
  • Partner with engineering and data science teams to design products leveraging machine learning models, generative AI capabilities, and large-scale data systems.
  • Oversee the development of intelligent product features such as automated insights, reporting systems, and decision-support tools built on structured and unstructured data sources.
  • Ensure solutions are designed for scalability, reliability, and integration within enterprise data ecosystems.
  • Manage product lifecycles in a technical environment, including backlog creation, prioritization, and delivery of features involving data pipelines, models, and platform components.
  • Balance business impact with technical feasibility and platform extensibility when making product decisions.
  • Translate complex technical concepts into clear product requirements and stakeholder communications, enabling alignment across technical and non-technical teams.
  • Collaborate with cross-functional teams including Engineering, Data Science, UX, and Analytics to deliver production-ready solutions and continuously improve product capabilities.
  • Assess market trends and emerging technologies in AI/ML and analytics to inform product direction and maintain competitive positioning.
  • Establish standards for data-driven products and reporting solutions, ensuring consistency, scalability, and long-term usability across teams.
  • Support team development by guiding best practices in technical product management and execution.

Minimum Qualifications:

  • Must be eighteen years of age or older.
  • 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 and 3 years of experience in a related occupation. Requires 3 years of experience in the following skills:
  • Product management experience in enterprise AI/ML, automations, and data platform environments;
  • Translating business requirements into machine learning or advanced analytics solutions;
  • Developing, evaluating, and deploying models in production environments with data science teams
  • Working with cloud-based data and analytics platforms (e.g., SQL, IBM Cloud, or similar technologies);
  • Managing products built on large-scale structured and unstructured datasets;
  • Building or scaling data-driven products, analytics platforms, or reporting systems;
  • Developing AI-powered insights, dashboards, or decision-support tools;
  • Working within modern Agile software development environments for data and AI products;
  • Creating and managing complex product backlogs involving data pipelines, models, and platform components;
  • Conducting user research and translating findings into product requirements and technical specifications;
  • Working with cross-functional teams including Engineering, Data Science, UX, and Analytics; and
  • Conducting competitive analysis within AI/ML, data, or analytics product domains.

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