Staff, Data Scientist

Walmart Walmart · Retail · Bentonville, AR

Walmart is seeking a Staff Data Scientist to develop and deploy advanced AI/ML models, conduct cutting-edge research in AI including generative/agentic AI, and contribute to scientific publications. The role involves problem formulation, data exploration, model development, deployment, MLOps, and mentorship, with a focus on interpretability, scalability, and strategic impact. Experience with Python, cloud environments (GCP), MLOps tools, and transformers/embeddings is required.

What you'd actually do

  1. Design and develop state-of-the-art algorithms, AI/ML models, and optimization techniques to generate actionable business insights.
  2. Conduct cutting-edge research in machine learning, AI (including generative/agentic AI), optimization, and related areas.
  3. Model Deployment & MLOps: Validate and monitor AI/ML models post-deployment, leveraging MLOps best practices such as CI/CD pipelines, performance tuning, and effective systems integration.
  4. Contribute to scientific knowledge by publishing research in top-tier journals and conferences.
  5. Mentorship & Leadership: Mentor team members and interns, offering guidance on research methods, problem-solving, and career development.

Skills

Required

  • Python
  • Pandas/Polars
  • NumPy
  • PySpark
  • TensorFlow
  • PyTorch
  • GPU utilization
  • software development
  • mathematical/scientific computing
  • large-scale AI/ML/DS solutions
  • cloud compute environments (GCP)
  • MLOps
  • CI/CD pipelines
  • performance tuning
  • systems integration
  • Google Vertex
  • MLFlow
  • ClearML
  • ML pipelines
  • ETL/ELT data pipelines
  • data-driven applications
  • transformers
  • embeddings
  • DevOps tools
  • Git/GitHub/GitHub Actions
  • infrastructure-as-code methodologies
  • communication
  • stakeholder management

Nice to have

  • agentic and multi-agent frameworks
  • tool-use
  • retrieval-augmented generation
  • policy learning
  • safety mechanisms
  • evaluation harnesses
  • experimentation platforms
  • sequential decisioning
  • A/B testing
  • contextual bandits
  • uplift measurement
  • serverless architecture
  • microservices implementation
  • API Gateway
  • FastAPI
  • VM-hosted solutions
  • logistics
  • supply chains
  • delivery operations

What the JD emphasized

  • state-of-the-art algorithms
  • AI/ML models
  • optimization techniques
  • cutting-edge research
  • generative/agentic AI
  • publish research
  • Python
  • TensorFlow and/or PyTorch
  • GPU utilization
  • large-scale AI/ML/DS solutions
  • cloud compute environments
  • MLOps
  • ML pipelines
  • data-driven applications
  • transformers
  • embeddings

Other signals

  • Develop state-of-the-art algorithms, AI/ML models, and optimization techniques
  • Conduct cutting-edge research in machine learning, AI (including generative/agentic AI)
  • Contribute to scientific knowledge by publishing research in top-tier journals and conferences