(usa) Staff, Data Scientist

Walmart Walmart · Retail · Sunnyvale, CA

Staff Data Scientist at Walmart leading architecture and technical direction for large-scale Search and Personalization initiatives. Focuses on designing and deploying advanced AI solutions, including Generative AI, LLMs, and semantic search, to improve customer discovery and business outcomes. The role involves influencing technical strategy, mentoring senior scientists, and partnering across engineering and product teams to deliver scalable machine learning systems.

What you'd actually do

  1. Lead architecture and technical direction for Search and Personalization machine learning systems.
  2. Design scalable retrieval, ranking, recommendation, and personalization algorithms.
  3. Drive adoption of Generative AI, Large Language Models, embeddings, and semantic search capabilities.
  4. Lead cross-functional initiatives involving Product, Engineering, Platform, and Data Science teams.
  5. Establish experimentation frameworks and best practices for model development and evaluation.

Skills

Required

  • Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field.
  • Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field.
  • 6 years' experience in an analytics or related field

Nice to have

  • Data science
  • machine learning
  • optimization models
  • PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics
  • Successful completion of one or more assessments in Python, Spark, Scala, or R
  • Using open source frameworks (for example, scikit learn, tensorflow, torch)
  • knowledge of accessibility best practices

What the JD emphasized

  • Extensive experience building production AI/ML systems at scale.
  • Deep expertise in Search, Information Retrieval, Recommendation Systems, Personalization, or Ranking.
  • Experience with transformer models, embeddings, vector search, LLMs, or Generative AI applications.
  • Strong understanding of ML system architecture, MLOps, and distributed model deployment.
  • Expertise in experimentation, causal inference, and performance evaluation.

Other signals

  • production AI/ML systems at scale
  • Search, Information Retrieval, Recommendation Systems, Personalization, or Ranking
  • transformer models, embeddings, vector search, LLMs, or Generative AI applications
  • ML system architecture, MLOps, and distributed model deployment
  • experimentation, causal inference, and performance evaluation