Principal Data Scientist: Associate AI experience

About the role

The Associate AI Experiences team applies advanced data science, machine learning, and agentic AI to solve high-impact business problems across Walmart globally.

Responsibilities

• Build and deploy production ML systems end-to-end: data pipelines, feature stores, model training, serving layers, monitoring, and feedback loops at scale
• Provide technical vision and lead advanced development in agentic AI, reinforcement learning, and simulation
• 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
• Design agentic evaluation frameworks that benchmark agent performance across task completion, code quality, and multi-step reasoning accuracy
• Deploy NLP pipelines at enterprise scale — semantic similarity across millions of records using BERT/SBERT embeddings and vector search (FAISS)
• Lead high-impact projects end-to-end; problem framing, modeling, prototyping, production architecture, and rollout
• Author and review technical designs and standards; present findings to senior leadership
• Mentor senior scientists and engineers on advanced modeling techniques, feature engineering, and experimentation design - raising the technical bar across teams
• Influence roadmap prioritization and long-term strategy for AI and simulation capabilities
• Present insights to senior leadership with compelling data visualization, quantified business impact, and clear confidence intervals

Requirements

• 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

Qualifications

• Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field AND 5+ years’ experience in data science or Machine Learning roles with demonstrated impact
• PhD in AI, Machine Learning, Computer Science, Information Technology, Statistics, Applied Mathematics, Econometrics, or related field with relevant industry experience