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 Responsibilities:35% 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 implementation 30% 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 team 20% 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 advantage 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; 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. Direct Manager/ Direct Reports:This position 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:AI Orchestration: 4 years of experience in Data Science with a focus on Conversational AI, Gen. AI, agentic workflows, custom tool-calling, and reasoning traces (e.g., Lang. Smith). 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 B 2 B 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 Big. Query 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 Point 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:5 Preferred Years of Work Experience:No additional years of experience. Minimum Leadership Experience:None. Preferred Leadership Experience:None. Certifications:None. Competencies:Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needs. 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. Cultivates Innovation: Creating new and better ways for the organization to be successful. Customer Focus: Building strong customer relationships and delivering customer-centric solutions. Develops Talent: Developing people to meet both their career goals and the organization's goals. Directs Work: Provides direction, delegating and removing obstacles to get work done. 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. Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels