(usa) Staff, Data Scientist

Walmart · Retail · Bentonville, AR +1

Staff Data Scientist at Walmart to build and deploy large-scale Genai systems, leveraging LLMs and RAG for financial applications. The role involves developing data science systems, summarizing data, and collaborating with stakeholders to productionize solutions. Experience with model optimization, agent frameworks, and cloud platforms is required.

What you'd actually do

  1. Lead high-caliber team to build large-scale Genai systems
  2. Develop data science systems and tools for retail; e-commerce applications:
  3. Leverage LLMS to summarize and build large scale applications
  4. Establish cross-functional relationships to maintain win-win situation for the corporation
  5. Collaborate with various product stake holders and business owners to formulate and productionize a solution

Skills

Required

  • Master's degree or PHD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 7+ years' experience in the related field.
  • Strong solution architecture mindset
  • Experience with training and inference of large-scale AI models (LLMs, multimodal, reasoning models)
  • Knowledge of advanced model optimization techniques (quantization, pruning, distillation, Lora, PEFT)
  • Solid understanding of LLMs and Genai ecosystems
  • Hands-on experience with RAG, AI agent development, and frameworks (Lang Chain, Langgraph)

Nice to have

  • Experience with Big Data processing and feature engineering using Spark
  • Experience with training machine learning models through Cloud Services (GCP, Azure)
  • Hands on experience of designing and training large DL models on GPU

What the JD emphasized

  • Must have qualifications
  • Strong solution architecture mindset, with the ability to apply AI/ML technologies to solve complex business problems.
  • Experience with training and inference of large-scale AI models such as Large Language Models (LLMs), multimodal models, and reasoning models.
  • Knowledge of advanced model optimization techniques, including quantization, pruning, distillation, Low-Rank Adaptation (Lora), and Parameter-Efficient Fine-Tuning (PEFT) for cloud deployment.
  • Solid understanding of LLMs and Genai ecosystems, including GPT, Llama, Mistral, Claude, Gemini, AWS Sonnet, and related frameworks/tools.
  • Hands-on experience with RAG (Retrieval-Augmented Generation), AI agent development, and frameworks such as Lang Chain, Langgraph etc.,

Other signals

  • LLMs
  • Genai systems
  • RAG
  • AI agent development