Data Scientist - Generative BI
At a glance
Mid-level AI Research role at Homedepot. STORE SUPPORT CENTER · no salary stated · we estimate $135,000–$232,000 across the United States.
Homedepot has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Configure and improve generative BI capabilities, turning user feedback and analytics pain points into technical fixes
- Build semantic layers and curate example SQL queries so AI-generated answers have better context
- Create automated regression tests and connect enterprise data sources to a multi-agent architecture
- Develop analytical models for large datasets, then explain findings and recommendations to business and technical audiences
- Work with business partners to set project goals and create reusable, documented analytics solutions
What you bring
- A bachelor's degree or equivalent in a job-related field is required
- You are legally authorized to work in the United States and are at least eighteen years old
- At least three years of work experience, with business intelligence and analytics experience preferred
- Experience with scripting, querying data, generative AI, or the Databricks ecosystem is preferred
Who this fits
This role suits a hands-on data scientist who improves existing generative analytics rather than building generative models from scratch. You will work independently and may lead small projects, but the role has no direct reports. Overnight travel is typically under ten percent.
From the employer
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