Data Scientist - Generative BI

The Home Depot; Atlanta (GA); On-site; USD 120,000 - 160,000; Full time

Job summary

The Home Depot is seeking a Data Scientist - Generative BI to advance profitability and analytics across our enterprise. You will configure, tune, and scale GenBI capabilities, build semantic layers, curate sample SQL queries, and establish automated testing pipelines for AI-generated outputs.

You will leverage Databricks and big data sources to deliver robust data solutions, working with cross-functional teams to drive actionable insights and scalable analytics products.

Qualifications

• 4+ years in business intelligence and analytics.
• Experience with generative AI chatbots or conversational analytics.
• Strong programming in Python and data tooling.
• Experience running queries against large datasets (BigQuery/SQL).
• Familiarity with Databricks ecosystem and CI/CD practices.

Responsibilities

• Design and develop analytics solutions using large datasets to generate business insights.
• Communicate results to technical and non-technical stakeholders; influence decision-making.
• Collaborate with cross-functional teams to align goals and deliver data-driven outcomes.
• Continuously explore and build reusable data science assets and documentation.

Skills

Python

SQL

Databricks

LLMs / Generative AI

GitHub & CICD

Communication

Education

Bachelor's degree in a related field

Tools

Databricks

Google BigQuery

SQL

Job description

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

Position Purpose

The 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

• 55% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies
• 20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Present recommendations in a confident manner in order to influence execution of recommendation; 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
• 10% Business Collaboration - Incorporate business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Work with project teams and business partners to determine project goals
• 15% 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 replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented

Direct Manager/Direct Reports

• This position typically reports to 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 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.
• 4+ 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.

Minimum Education

• The knowledge, skills and abilities typically acquired through the completion of a bachelor’s degree program or equivalent degree in a field of study related to the job.

Preferred Education

• No additional education

Minimum Years of Work Experience

• 3

Preferred Years of Work Experience

• No additional years of experience

Minimum Leadership Experience

• None

Preferred Leadership Experience

• None

Certifications

• None

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