Senior Data Scientist – Supply Chain Optimization

Walmart • Bentonville, AR

22h • $110,302 - $180,000 • Onsite

About The Position

The Senior Data Scientist – Supply Chain Optimization designs and deploys intelligent agents and machine learning systems to optimize customer delivery promises, fulfillment routing, and root-cause analysis across end-to-end supply chain workflows. The role builds agents with reasoning, planning, tool-use, and short- and long-term memory, using frameworks such as LangChain, LangGraph, Google ADK, and Pydantic. It applies large language models and trainable model architectures to develop NLP solutions, including context engineering, chain-of-thought reasoning, and tool calling.

The position deploys AI, machine learning, and agentic systems into production using Docker, Kubernetes, GCP or Azure, Airflow, and CI/CD pipelines. It develops scalable RAG systems and manages vector databases and knowledge graphs to support access to logistics policies, procedures, and network constraints. The role also applies statistical and machine learning methods to structured and unstructured data, develops data workflows using PostgreSQL and BigQuery, and creates evaluation and observability frameworks to monitor production performance, accuracy, hallucinations, latency, and cost. It translates AI research into scalable enterprise solutions that improve the end-to-end supply chain.

The position is located at 811 Excellence Dr, Bentonville, AR 72716. Pay is $110,302–$180,000 per year, with additional annual or quarterly performance incentives. The employer accepts any amount of graduate coursework, graduate research experience, or professional experience with the required skills.

Requirements

• Bachelor’s degree or equivalent in Computer Science, Analytics, Engineering, or a related field, plus at least 1 year of experience in analytics or a related field; or a master’s degree or equivalent in one of those fields.
• Experience building deep learning model architectures in Python using PyTorch, TensorFlow, and LangChain.
• Experience pre-training or fine-tuning language models from Hugging Face or TFHub for NLP tasks such as natural language inference and question answering, using open-source corpora such as SQuAD and MNLI.
• Experience with generative models such as OpenAI GPT and encoder-based models such as BERT, RoBERTa, and DistilBERT for language-based reasoning problems.
• Experience with computational semantics tools such as WordNet, spaCy, and NLTK.
• Experience with advanced statistical and modeling methods, including graphical models, Bayesian inference, neural networks, SVMs, and Random Forest, using scikit-learn and SciPy.
• Experience with model assessment and validation techniques, including testing, tuning, chi-square, ROC curves, and root mean square error.
• Experience performing trend, sentiment, and cluster analysis to address business problems and provide recommendations and insights; familiarity with Word2Vec, TF-IDF, K-Means, hierarchical clustering, PCA, and FAMD.
• Experience conducting exploratory data analysis using Pandas, NumPy, Matplotlib, and Plotly.
• Experience with CI/CD, software testing, and documentation, including UML, state and activity workflows, Astah, and Java.

Responsibilities

• Design and deploy goal-driven agents for customer delivery promises, fulfillment routing, and supply-chain root-cause analysis.
• Build agents with reasoning, planning, tool-use, and short- and long-term memory capabilities.
• Develop NLP solutions using large language models and trainable model architectures.
• Deploy AI, machine learning, and agentic systems into production environments.
• Use Docker, Kubernetes, cloud platforms, Airflow, and CI/CD pipelines to support scalability, reliability, low latency, and continuous improvement.
• Build scalable retrieval-augmented generation systems for access to logistics policies, procedures, and network constraints.
• Manage vector databases and knowledge graphs to improve decision accuracy in fulfillment, routing, and issue resolution.
• Apply classical and advanced machine learning methods to structured and unstructured datasets to improve delivery ETA prediction and reliability.
• Build and optimize data workflows using PostgreSQL and Google BigQuery, ensuring data quality, consistency, and performance.
• Develop evaluation and observability frameworks to measure model and agent performance, decision accuracy, hallucination rates, latency, and cost.
• Translate advances in AI research into production-ready enterprise solutions for the end-to-end supply chain.

Benefits

• Medical, vision, and dental coverage.
• 401(k), stock purchase, and company-paid life insurance.
• Paid time off, including sick leave, parental leave, family care leave, bereavement leave, jury duty leave, and voting leave.
• Short-term and long-term disability.
• Education assistance, including company-paid college degrees.
• Company discounts.
• Military service pay.
• Adoption expense reimbursement.
• Annual or quarterly performance incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior