Principal Data Scientist: Associate AI Experience

Walmart · Retail · Bentonville, AR +2

Principal Data Scientist to provide technical leadership and long-term vision for next-generation AI systems and platforms. This role will drive breakthrough system design and advanced solution development, transforming Walmart at scale. The role combines deep technical expertise (ML, simulation, optimization, agentic AI) with cross-functional influence, mentoring of senior talent, and delivery of high-impact, productionized solutions. The team applies advanced data science, machine learning, and agentic AI to solve high-impact business problems across Walmart globally, building production Agentic systems, deploying autonomous AI agents, and translating complex data into actionable insights.

What you'd actually do

  1. Build and deploy production ML systems end-to-end: data pipelines, feature stores, model training, serving layers, monitoring, and feedback loops at scale
  2. Provide technical visionand lead advanced development in agentic AI, reinforcement learning, and simulation.
  3. Architect and deploy large-scale AI systems and autonomous AI agents — conversational assistants, predictive agents with tool-calling, and multi-agent orchestration systems using LangChain, Pydantic AI, and RAG patterns
  4. Design agentic evaluation frameworks that benchmark agent performance across task completion, code quality, and multi-step reasoning accuracy
  5. Deploy NLP pipelines at enterprise scale — semantic similarity across millions of records using BERT/SBERT embeddings and vector search (FAISS)

Skills

Required

  • Deep expertise in ML algorithms (XGBoost, CatBoost, LightGBM, Random Forest, AutoML) and deep learning (PyTorch, transformer architectures).
  • Production experience with NLP (BERT, SBERT, FAISS, RAG), computer vision (YOLO, CLIP), and time series forecasting (ARIMA, Prophet).
  • Hands-on experience building and orchestrating multiple AI agents with LangChain, RAG, tool integration, and memory management.
  • Multi-cloud ML platform proficiency — AWS SageMaker AND GCP (Vertex AI, BigQuery, BigQuery ML).
  • Strong Python skills (Pandas, NumPy, Scikit-learn) with containerization (Docker) and MLOps practices.
  • Advanced statistical analysis, experiment design, and causal inference
  • Experience deploying production-grade AI systems at scale.
  • Ability to translate complex analytical results into clear business recommendations for non-technical stakeholders.

Nice to have

  • PhD in AI, Machine Learning, Computer Science, Information Technology, Statistics, Applied Mathematics, Econometrics, or related field with relevant industry experience.

What the JD emphasized

  • architect end-to-end ML/AI systems
  • built and shipped multiple autonomous AI agents
  • ship production systems through AI-assisted development
  • production Agentic systems
  • deploy autonomous AI agents
  • agentic AI
  • autonomous AI agents
  • multi-agent orchestration systems
  • agentic evaluation frameworks
  • Deploy NLP pipelines at enterprise scale
  • deploy production-grade AI systems at scale

Other signals

  • Build and deploy production ML systems end-to-end
  • Architect and deploy large-scale AI systems and autonomous AI agents
  • Design agentic evaluation frameworks
  • Deploy NLP pipelines at enterprise scale