Sr. Data Scientist, Contact Center AI

Senior Data ScientistWith a career at The Home Depot, you can be yourself and also be part of something bigger.The Senior Data Scientist will be a key architect in building next-generation agentic systems designed to revolutionize how professional customers manage complex projects. This role is responsible for developing autonomous AI capabilities that bridge the gap between simple search and sophisticated project quoting and fulfillment. You will leverage advanced techniques in Conversational AI, Retrieval-Augmented Generation (RAG), and Multimodal AI to unlock vast enterprise catalogs, automate project and product configuration, and provide real-time sourcing across a massive enterprise assortment.As a senior member of the team, you will design the reasoning paths that allow AI agents to navigate "Pro-speak" queries, extract intent from multimodal project inputs, and manage complex state across omnichannel sessions.

Your work will directly empower Pro customers to move from discovery to optimized quoting to transaction in minutes, providing a seamless, self-serve experience at scale.Key Responsibilities35% Solution Development - Proficiently 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 implementation30% Project Management & Team Support - 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 team20% Business Collaboration - 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 advantage15% 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; 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 documentedTravel RequirementsTypically requires overnight travel less than 10% of the time.Physical RequirementsMost 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 ConditionsLocated in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.Minimum QualificationsMust be eighteen years of age or older.Must be legally permitted to work in the United States.Preferred QualificationsAI Orchestration: 4+ years of experience in Data Science with a focus on Conversational AI, GenAI, agentic workflows, custom tool-calling, and reasoning traces (e.g., LangSmith).Advanced Retrieval: Mastery of RAG and vector database architectures, specifically for extracting technical specs from unstructured enterprise data.Multimodal AI: Experience building pipelines to extract structured SKU-level intent from unstructured multimodal inputs, such as photos or handwritten lists.Algorithmic Logic: Background in similarity scoring and attribute-matching to resolve vague technical queries.State & Engineering: Experience building stateful AI applications that maintain context across devices and sessions.Domain Expertise: Prior experience in B2B e-commerce, supply chain, or trade-related data is a significant plus.Technical Expertise: Experience in a modern scripting language (preferably Python); proficient running queries against data (preferably with Google BigQuery or SQL); proficient utilizing statistical techniques to identify key insights that help solve business problems; knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP; working knowledge of Microsoft Excel and Power PointMinimum EducationThe 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 EducationNo additional educationMinimum Years of Work Experience5Preferred Years of Work ExperienceNo additional years of experienceMinimum Leadership ExperienceNonePreferred Leadership ExperienceNoneCertificationsNoneCompetenciesAttracts Top Talent: Attracting and selecting the best talent to meet current and future business needsBusiness Insight: Applying knowledge of the business and the marketplace to advance the organization's goalsCollaborates: Building partnerships and working collaboratively with others to meet shared objectivesCommunicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiencesCultivates Innovation: Creating new and better ways for the organization to be successfulCustomer Focus: Building strong customer relationships and delivering customer-centric solutionsDevelops Talent: Developing people to meet both their career goals and the organization's goalsDirects Work: Provides direction, delegating and removing obstacles to get work doneDrives Results: Consistently achieving results, even under tough circumstancesNimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodderOptimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvementSelf-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels