Associate Data Scientist - Generative BI

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

The Associate Data Scientist - Generative BI will drive business profitability and modernized analytics across Home Depot by configuring, tuning, and scaling our GenBI capabilities. Rather than building generative models from scratch, your day-to-day work focuses on practical AI enablement: translating user feedback and analytical friction into robust technical solutions. You will build and maintain rich semantic layers, curate golden SQL query examples to maximize context accuracy, establish automated regression testing pipelines to validate AI-generated answers, and integrate new enterprise data sources into a scalable multi-agent architecture. Success in this role requires a proactive problem-solver who can leverage every tool in the Databricks ecosystem to resolve data quality issues, troubleshoot integration risks, and adapt as underlying platform features evolve.

Key Responsibilities

• 70% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Supports data science projects by conducting effective analysis to solve business problems; Executes tasks with high levels of efficiency and quality; Consults with Data Scientist or Sr. Data Scientist on appropriate selection, utilization and interpretation of advanced analytical methodologies; Learn about the assigned business areas to provide better solutions by incorporating business-specific knowledge
• 20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical audience; Support preparation of reports, updates and/or presentations related to progress made on a project or solution; Highlights potential impacts of recommendations to drive alignment and appropriate implementation
• 10% Technical Learning - Keep up to date on industry trends, best practices and emerging methodologies; Continually develop skills and expertise in data analytics concepts and methodologies; Identify opportunities to apply learnings

Travel Requirements

• No travel required.

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 articles.

Working Conditions

• Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications

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

Preferred Qualifications

• Master's degree in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience.
• 3+ years of experience in business intelligence and analytics.
• Experience in a modern scripting language (preferably Python).
• Experience running queries against data (preferably with Google BigQuery or SQL).
• Experience with generative AI chatbots, large language models (LLM) or conversational analytics.
• Experience with the Databricks ecosystem.
• Experience utilizing statistical techniques, predictive modeling, data mining and data analysis to identify key insights that help solve business problems.
• Experience with GitHub Repositories and standard CICD practices.

Competencies

• Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm
• 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
• Customer Focus: Building strong customer relationships and delivering customer-centric solutions
• 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
• Plans and Aligns: Planning and prioritizing work to meet commitments aligned with organizational goals
• Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels