Senior, Data Scientist

What you ll do

As a Senior Data Scientist at Sam’s Club Applied AI/ML Labs
, you will lead the design, development, and deployment of AI agents powered by LLMs and ML/DL models
.

You will be responsible for creating production-grade AI agents that drive measurable business impact in retail — from operations and merchandising to finance, conversational AI, and e-commerce. Success in this role requires not only deep technical expertise but also the ability to collaborate closely with product and business teams to ensure AI solutions are reliable, responsible, and strategically aligned
.

About Team: Sam s Club is our membership warehouse club, a business model that provides our members with high-quality products at prices that are unrivaled by traditional retail. Sam s Club provides a carefully curated assortment of items, as well as developing and leading technologies and services such as Scan & Go, Club Pickup, and home delivery service in select markets.

Sam s Club also provides travel, auto purchasing, pharmacy, optical, hearing aid centers, tire and battery centers, and a portfolio of business operations support services.

What you ll do:

• Design & Deploy AI Agents: Lead the development of agentic AI systems and AI agents
  , building capabilities such as reasoning, orchestration, memory, RAG, and automated evaluation.
• Integrate with Business Systems: Build AI agents that can connect to tools, APIs, and enterprise systems
  , ensuring seamless integration into real-world workflows.
• Evaluation & Safety: Establish evaluation frameworks (automated + human-in-the-loop) to measure reliability, robustness, factual grounding, and safety of AI agents in production.
• Production-Grade Deployment: Architect, prototype, and deploy AI agents and ML systems into large-scale production environments using modern MLOps and observability practices
  .
• Prompting & Fine-Tuning: Apply advanced prompt engineering, instruction design, and parameter-efficient fine-tuning (LoRA, PEFT, etc.) to optimize LLM behavior for business use cases.
• Advance Traditional ML/DL: Apply statistical modeling, causal inference, and classical ML and Deep Learning methods to complement LLM-based approaches where needed.
• Mentor & Lead: Provide technical guidance to junior scientists, setting standards for building, testing, and deploying AI agents.
• Responsible AI: Partner with product and business stakeholders to ensure AI agents are designed with transparency, ethics, and governance at the forefront.

What you ll bring:

• Agentic AI Expertise: Proven hands-on experience building and deploying AI agents in production, with deep knowledge of reasoning frameworks, orchestration tools, and memory systems.
• Evaluation & Safety: Experience creating evaluation pipelines and safety guardrails for AI agents, including methods to detect hallucination and ensure factual accuracy.
• Framework Proficiency: Familiarity with agent orchestration frameworks (e.g., Lang Chain, Llama Index, Haystack) and vector databases (FAISS, Pinecone, Weaviate) for RAG and memory.
• Strong ML Foundations: Solid grounding in machine learning, statistics, and causal inference, with experience applying both traditional ML and modern LLM-based methods. Understanding of advanced ML topics such as Deep Learning (ENN, CNN, RNN, etc.), GAN, Transformers, NLP.
• Prompting & Fine-Tuning: Expertise in prompt engineering, system instruction design, and fine-tuning techniques (LoRA, PEFT, RLHF/RLAIF a plus).
• MLOps & Observability: Strong background in CI/CD pipelines, monitoring, logging, and observability for deployed AI/ML systems.
• Big Data: Experience working with large datasets, finding insights, and storytelling with data. Proficiency with distributed data stores (e.g., SQL, No
  
  SQL) and cloud technologies like GCP Big Query.
• Cloud: E2E pipeline development experience in cloud environments, preferably with GCP including Vertex AI, Dataproc, Airflow, etc.
• Programming
  
  Skills:
  
  Proficiency in Python, SQL, PyTorch/Tensor Flow, Hugging Face, and distributed computing frameworks (PySpark).
• Business Acumen: Ability to translate business challenges into AI solutions and communicate technical concepts clearly to non-technical partners.
• Leadership & Communication: Experience mentoring data scientists and collaborating cross-functionally in agile environments.
• Preferred: Experience in retail and merchandising domain (assortment, pricing, space, planogram etc).

About Walmart Global Tech Think about an environment where one line of code can impact hundreds of millions of people. We are a team of software engineers, data scientists, cybersecurity specialists and service professionals at the world s leading retailer. We are people-led and tech-empowered, with opportunities to grow and build foundational skills for the future of retail.

Walmart s culture emphasizes collaboration and in-person teamwork to move fast. Our hubs include locations across the U.S. and around the world, with global headquarters in Bentonville, AR.

Benefits: Beyond a competitive…