Sam’s Club
Overview
This range is provided by Sam's Club. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range
$90,000.00/yr - $180,000.00/yr Position Summary
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 requires deep technical expertise and the ability to collaborate with product and business teams to ensure AI solutions are reliable, responsible, and strategically aligned. 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 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., LangChain, LlamaIndex, 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 (Deep Learning, 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 with large datasets, distributed datastores (SQL, NoSQL), and Big Data/Cloud technologies like GCP BigQuery. Cloud: End-to-end pipeline development experience in cloud environments, preferably with GCP including Vertex AI, Dataproc, Airflow, etc. Programming Skills: Python, SQL, PyTorch/TensorFlow, HuggingFace, 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). About Walmart Global Tech
Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That’s what we do at Walmart Global Tech. We’re a team of software engineers, data scientists, cybersecurity experts, and service professionals within the world’s leading retailer who make an epic impact and are at the forefront of the next retail disruption. We are people-led and tech-empowered, and we train our team in the skillsets of the future. Walmart’s culture is a competitive advantage, fostered by being together. We use our campuses to create purposeful connection rooted in deepening understanding and investing in the development of our associates. Our hubs include Bentonville, AR; San Francisco Bay Area; and New York/New Jersey. Benefits & Equal Opportunity
Benefits: Beyond our great compensation package, incentive awards for performance, 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and more. Equal Opportunity Employer: Walmart, Inc. is an Equal Opportunity Employer – By Choice. We value diverse styles, experiences, identities, ideas, and opinions and are inclusive of all people. The above information is a general description of the role and is not exhaustive. The full Job Description can be made available as part of the hiring process. Additional notes
Minimum Qualifications: See listed options (Bachelor’s or Master’s with years of analytics experience) or equivalent experience. Preferred Qualifications: Data science, ML, optimization models, Python/Spark/Scala/R, open source frameworks, accessibility best practices align with Walmart’s accessibility standards.
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This range is provided by Sam's Club. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range
$90,000.00/yr - $180,000.00/yr Position Summary
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 requires deep technical expertise and the ability to collaborate with product and business teams to ensure AI solutions are reliable, responsible, and strategically aligned. 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 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., LangChain, LlamaIndex, 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 (Deep Learning, 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 with large datasets, distributed datastores (SQL, NoSQL), and Big Data/Cloud technologies like GCP BigQuery. Cloud: End-to-end pipeline development experience in cloud environments, preferably with GCP including Vertex AI, Dataproc, Airflow, etc. Programming Skills: Python, SQL, PyTorch/TensorFlow, HuggingFace, 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). About Walmart Global Tech
Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That’s what we do at Walmart Global Tech. We’re a team of software engineers, data scientists, cybersecurity experts, and service professionals within the world’s leading retailer who make an epic impact and are at the forefront of the next retail disruption. We are people-led and tech-empowered, and we train our team in the skillsets of the future. Walmart’s culture is a competitive advantage, fostered by being together. We use our campuses to create purposeful connection rooted in deepening understanding and investing in the development of our associates. Our hubs include Bentonville, AR; San Francisco Bay Area; and New York/New Jersey. Benefits & Equal Opportunity
Benefits: Beyond our great compensation package, incentive awards for performance, 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and more. Equal Opportunity Employer: Walmart, Inc. is an Equal Opportunity Employer – By Choice. We value diverse styles, experiences, identities, ideas, and opinions and are inclusive of all people. The above information is a general description of the role and is not exhaustive. The full Job Description can be made available as part of the hiring process. Additional notes
Minimum Qualifications: See listed options (Bachelor’s or Master’s with years of analytics experience) or equivalent experience. Preferred Qualifications: Data science, ML, optimization models, Python/Spark/Scala/R, open source frameworks, accessibility best practices align with Walmart’s accessibility standards.
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