Senior Data Scientist, Assortment and Space Planning

Position Purpose: Join us in revolutionizing merchandise decision-making through cutting-edge AI-powered solutions and automation. As a Senior Data Scientist, you will play an essential role in architecting and constructing advanced GenAI and Agentic AI Systems that facilitate autonomous decision recommendations. This position emphasizes the orchestration of large language models (LLMs) alongside existing foundational models to create adaptive, learning decision systems that enhance operational efficiency and elevate customer experiences. In this role, you will lead the comprehensive implementation of agentic AI projects, managing everything from architectural design and experimentation to evaluation and production governance. Collaborating closely with data science teams, product managers, software engineers, and business stakeholders, you will integrate foundational science models into agentic workflows, design AI orchestration platforms, and foster scalable production service frameworks. You will establish best practices and standards for Agentic AI development, offer insights to diverse audiences, and provide strategic technical leadership across cross-functional teams. Key Responsibilities: Solution Development (30%): Leverage your expertise to design and develop algorithms and models that generate meaningful business insights from large datasets. Choose, utilize, and interpret advanced analytics methodologies effectively. Communicate insights and recommendations clearly to both technical and non-technical leaders and business partners, ensuring alignment and proper implementation. Project Management & Team Support (25%): Lead and manage complex projects and coordinate teams. Guide prioritization of tasks and ensure high-quality outcomes. Mentor junior team members to enhance their technical skills. Collaborate with management in resource allocation and workload distribution. Act as a technical subject matter expert in predictive and prescriptive data science methods, while promoting data science communities across various business units. Business Collaboration (20%): Utilize your extensive business acumen to inform your solution approach. Build trust and collaboration with internal customers and cross-functional teams. Provide advanced analytics education to the data science community, and work with IT to explore new tools that maintain technical agility. Actively pursue new business opportunities where data science can provide a competitive edge. Technical Exploration & Development (25%): Stay updated on key data science developments by attending conferences and publishing papers. Contribute to ongoing improvement in analytics by developing replicable solutions, such as codified data products and project documentation. Establish best practices and a clear vision for data analysis and model productionalization. Maintain a library of reusable algorithms and ensure code/model documentation. Achieve proficiency in one or more prescriptive modeling techniques, such as optimization, computer vision, recommendation systems, search, or NLP. Direct Manager/Direct Reports: This position typically reports to a manager or higher. This role has no direct reports but leads and manages projects. Travel Requirements: Occasionally requires overnight travel, generally less than 10% of the time. Physical Requirements: Primarily involves sitting comfortably with opportunities for movement. Rarely may require light lifting or relocation of items. Working Conditions: Located in a comfortable indoor environment; rare instances of unpleasant conditions are manageable. Minimum Qualifications: Must be at least eighteen years old. Must be authorized to work in the United States. Proven expertise in predictive modeling, data mining, and data analysis. Demonstrated experience using statistical techniques to extract significant insights that address business challenges. Preferred Qualifications: Over 10 years of cumulative experience in AI engineering, software engineering, or ML engineering. At least 2 years of hands-on experience developing and deploying GenAI or LLM-driven automated systems, and Agentic AI evaluation frameworks at scale. Familiarity with LLM agent orchestration frameworks (e.g., LangGraph, LangChain). Strong grasp of structured agent interactions (e.g., MCP and A2A). Experience deploying models and APIs in containerized, cloud-neutral environments. Expertise in prompt engineering, RAG implementation, and LLM fine-tuning. Knowledge of agentic IDEs (e.g., GitHub Copilot, Cursor). Experience with the Google Cloud Platform (GCP). Practical knowledge of vector databases and exposure to knowledge graphs (e.g., Neo4j), embeddings, or multimodal data ingestion. Able to collaborate with front-end developers or create simple UI prototypes (e.g., Streamlit, React). Contributed to open-source AI/ML tools or orchestration frameworks. Experience in the merchandising, retail, e-commerce, or supply chain domain. Minimum Education: Knowledge, skills, and abilities typically gained through the completion of a bachelor's degree program or an equivalent qualification in a relevant field of study. Preferred Education: No additional education preferred. Minimum Years of Work Experience: 10 years. Preferred Years of Work Experience: No additional years preferred. Minimum Leadership Experience: None required. Preferred Leadership Experience: None required. Certifications: None required. Competencies: Attracting Top Talent: Ability to attract and select the best talent for current and future business needs. Building Networks: Skill in establishing formal and informal relationships within and outside the organization. Business Insight: Applying knowledge of the business and marketplace to further organizational goals. Collaboration: Working effectively with others to achieve shared objectives. Effective Communication: Conveying complex information clearly to diverse audiences. Innovation: Creating new strategies for organizational success. Talent Development: Helping others meet their career and organizational goals. Trust Building: Earning the confidence of others through integrity and authenticity. Optimizing Work Processes: Applying efficient methods for achieving goals with a focus on continuous improvement. Persuasiveness: Gaining support and commitment through compelling arguments. Self-Development: Seeking opportunities for personal growth and professional challenges. Strategic Thinking: Anticipating future possibilities and developing strategies for success. Technical Agility: Adopting innovations in technology and digital applications to enhance business performance. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment based on race, color, sex, age, national origin, religion, sexual orientation, gender identity, veteran status, disability, or any other federal, state, or local protected class.

Created: 2026-03-04