Senior Data Scientist - Generative BI

The Home Depot•Atlanta, GA

About The Position

The Senior 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.

Requirements

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

Nice To Haves

PhD in a quantitative field (Computer Science, Math, Statistics, etc.)
6+ 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.
No additional education
No additional years of experience
No certifications

Responsibilities

Design and develop algorithms and models to use against large datasets to create business insights.
Execute tasks with high levels of efficiency and quality.
Make appropriate selection, utilization and interpretation of advanced analytical methodologies.
Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners.
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.
Work with project teams and business partners to determine project goals.
Provide direction on prioritization of work and ensure quality of work.
Provide mentoring and coaching to more junior roles to support their technical competencies.
Collaborate with managers and team in the distribution of workload and resources.
Support recruiting and hiring efforts for the team.
Leverage extensive business knowledge into solution approach.
Effectively develop trust and collaboration with internal customers and cross-functional teams.
Provide general education on advanced analytics to technical and non-technical business partners.
Deep understanding of IT needs for the team to be successful in tackling business problems.
Actively seek out new business opportunities to leverage data science as a competitive advantage.
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.
Define best practices and develop clear vision for data analysis and model productionalization.
Contribute to library of reusable algorithms for future use, ensuring developed codes are documented.