Director, Data Science

Walmart · Retail · Sunnyvale, CA

Director of Data Science for Walmart International's Personalization team, focusing on leading the strategy, development, and scaling of AI-powered personalization systems. This role involves driving innovation in recommendation systems, relevance, and customer experience using LLMs, embeddings, RAG, and agentic AI frameworks, and managing a team of data scientists, researchers, and ML engineers to deliver measurable business outcomes.

What you'd actually do

  1. Define Personalization Strategy
  2. Lead Advanced AI & Personalization Systems
  3. Architect Scalable AI Platforms
  4. Establish Experimentation & Measurement Frameworks
  5. Champion Responsible AI & Governance

Skills

Required

  • 12+ years of experience in data science and machine learning
  • 5+ years in leadership roles
  • Proven success building and scaling personalization, recommendation, or search systems in large-scale environments
  • Deep expertise in Generative AI (LLMs, RAG, embeddings) and modern ML techniques such as reinforcement learning and contextual bandits
  • Strong experience with cloud-based ML platforms (preferably GCP), distributed data systems, and MLOps practices
  • Hands-on proficiency in Python, PyTorch/TensorFlow, and large-scale data processing (e.g., Spark, BigQuery)
  • Strong product mindset
  • Excellent communication and leadership skills

Nice to have

  • Experience with agentic AI systems, multi-agent architectures, or conversational AI
  • Background in global or multi-market personalization platforms
  • Experience building real-time personalization or recommendation systems at scale

What the JD emphasized

  • AI-powered personalization systems
  • recommendation systems
  • relevance
  • customer experience
  • LLMs
  • agentic AI frameworks
  • personalization, recommendation, or search systems
  • Generative AI (LLMs, RAG, embeddings)
  • agentic AI systems
  • global or multi-market personalization platforms
  • real-time personalization or recommendation systems at scale

Other signals

  • leading AI-powered personalization systems
  • driving innovation across recommendation systems, relevance, and customer experience
  • leveraging advanced machine learning, LLMs, and agentic AI frameworks
  • delivering highly relevant and contextual experiences for millions of customers globally
  • translating cutting-edge AI innovation into measurable business outcomes