Data Scientist

Position Overview
At Sam’s Club, we are building the next generation of autonomous commerce. The gap between raw data and agentic action is the Semantic Layer—and you are the architect of that bridge. As a Staff Data Scientist, you are the high‑level Individual Contributor responsible for ensuring our data is not just "stored," but agent‑consumable, leading the transition from traditional data architectures to a context‑aware world model that empowers AI agents to reason, plan, and execute complex member tasks with zero friction.

• Architect Agent‑Ready Data:
  Lead the scientific strategy for building the context and semantic layer, defining how structured, semi‑structured, and unstructured data are unified into Knowledge Graphs, Embeddings, and Metadata layers that power agentic reasoning.
• Lead the Agentic Transformation:
  Act as the technical "North Star" for the organization, ensuring every data product is optimized for Tool‑Calling, Retrieval‑Augmented Generation (RAG), and Multi‑Step Planning.
• Evaluate the "Latest and Greatest":
  Constantly scout the frontier of AI research, assessing emerging frameworks such as Lang Graph, Auto Gen, and Graph
  
  RAG to shape the Sam’s Club agentic stack.
• Bridge Science and Engineering:
  Act as the "technical glue," working with Engineering Managers and Data Scientists to ensure pipelines deliver the required semantic richness and reasoning density for our model‑driven agents.
• Design Reasoning Scaffolding:
  Develop methodologies for Context Enrichment, ensuring agents possess the right "mental model" of the member, inventory, and business logic at every decision point.
• Define Quality for Agents:
  Create evaluation frameworks that measure Semantic Precision, Retrieval Relevancy, and Reasoning Trajectory Success, keeping our agents grounded and hallucination‑free.

• Advanced Technical Standing: 7–10+ years in Data Science, Applied ML, or Semantic Engineering with a proven track record of deploying complex, model‑driven systems into production.
• Agentic Ecosystem Expertise:
  Hands‑on experience with vector databases (Pinecone, Milvus), graph databases (Neo4j), and LLM orchestration.
• Semantic Mastery:
  Expert understanding of ontology design, knowledge‑graph construction, and embedding‑space optimization.
• Hybrid Skillset:
  Comfortable discussing probabilistic models ($P(Action|Context)$) and optimizing Spark jobs or Big Query schemas.
• Engineering Mindset:
  Fluency in Python, Java, or Scala with deep knowledge of schema choices, latency, and data density impacts on autonomous agents.
• Collaborative Influence:
  Proven ability to lead through influence, aligning cross‑functional teams around a shared technical vision.

• Intelligence: LLMs (OpenAI, Gemini, Anthropic), Lang Chain/Llama Index, Lang Graph.
• Data & Context:
  Big Query, Dataflow, Neo4j, vector databases, Spark/PySpark.
• Decision Science:
  Reinforcement learning, contextual bandits, ranking and retrieval.

• Competitive base salary ranging from $ to $, with additional performance‑based bonuses.
• Regional Pay Zone (RPZ) adjustments based on location.
• Health benefits:
  
  medical, vision and dental coverage.
• Financial benefits:
  
  401(k), stock‑purchase plan and company‑paid life insurance.
• Paid time off: PTO, parental leave, family care leave, bereavement, jury duty, and voting. PTO/PPTO may be used for vacation, sick leave or holidays.
• Other benefits: short‑term and long‑term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more.
• Live Better U: fully paid education benefit for full‑time and part‑time associates, covering tuition, books and fees for a wide range of programs.
• Additional compensation includes annual or quarterly performance bonuses.

• Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years’ experience in an analytics‑related field.
• Master’s degree in the same areas and 2 years’ experience in an analytics‑related field.
• 6 years’ experience in an analytics or related field.

• Data science, machine learning, and…