Senior Data Scientist – Supply Chain Optimization
Reads like a ML Engineer role: putting models into production.
Bentonville, AR
- Pay
$110,302–180,000/year — pay source
Skills Required: Must have experience with: Building Deep Learning Model Architectures in Python using PyTorch, TensorFlow and Langchain; Pre-training/Fine-tuning language models (from HuggingFace, TFHub) for Natural Language Processing tasks (Natural Language Inference, Question-Answering etc.) with open-source corpora (SQUAD, MNLI, etc.); Generative models (OpenAI – GPT - X) and Encoder based models (BERT, RoBERTa, DistilBERT) for solving language-based reasoning problems; Computational semantics tools (WordNet, SpaCy, NLTK) for linguistic analysis; Advanced statistical and modelling methods (e.g., graphical models, Bayesian inference, neural networks, SVM, Random Forest etc.) using scikit-learn, scipy; Model Assessment and Validation: testing, tuning, and validation techniques (Chi square, ROC curve, root mean square error etc.); Performing trend, sentiments and cluster analysis on data to answer practical business problems and provide recommendations, key insights to business (Embeddings: Word2Vec, TFIDF) (Clustering Algorithms, KMeans, hierarchical Clustering) (Dimensionality Reduction (PCA, FAMD); Conducting exploratory data analysis activities using Pandas, Numpy, Matplotlib, Plotly; CI/CD, testing, and documentation in software development (UML, State and Activity workflows, Astah, Java). Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills. Rate of pay: $110,302.00 - 180,000.00/year. Additional compensation includes annual or quarterly performance incentives. Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign and deploy goal-driven agents for delivery promises, fulfillment routing, and root-cause analysis
Build scalable RAG systems for real-time access to logistics policies, SOPs, and network constraints
Apply classical and advanced ML to large datasets to improve delivery ETA prediction and reliability
Deploy AI/ML and agentic systems into production using Docker, Kubernetes, cloud platforms and Airflow
Build evaluation and observability frameworks to measure agent accuracy, hallucination rates, latency, and cost
From the employer’s posting
Design and deploy intelligent, goal-driven agents to optimize customer delivery promises, fulfillment routing, and root-cause-analysis
Build scalable Retrieval-Augmented Generation (RAG) systems to enable real-time access to logistics policies, SOPs, and network constraints.
Apply classical and advanced machine learning techniques (XGBoost, K-Means Clustering, Regression, SVMs, Random Forest etc.) on large-scale structured and unstructured datasets to drive improvements delivery ETA prediction and reliability.
Utilize Docker, Kubernetes, cloud platforms (GCP/Azure) and Airflow to ensure scalability, reliability, and low latency
Develop evaluation and observability frameworks using tools like Arize Phoenix and LangFuse to measure model and agent performance in production, accuracy of decisions, hallucination rates, latency, and cost.
Tools in this posting
- Java
- Python
- Azure
- BigQuery
- Docker
- GCP
- Kubernetes
- PostgreSQL
- Airflow
- Hugging Face
- Matplotlib
- NumPy
- pandas
- Plotly
- PyTorch
- scikit-learn
- SciPy
- TensorFlow
- XGBoost
Source — Tool mentions in context
Minimum education and experience required: Bachelor’s degree or the equivalent in Computer Science, Analytics, Engineering (any), or related field plus 1 years of experience in analytics or a related field; OR Master’s degree or the equivalent in Computer Science, Analytics, Engineering (any), or related field. Skills Required: Must have experience with: Building Deep Learning Model Architectures in Python using PyTorch, TensorFlow and Langchain; Pre-training/Fine-tuning language models (from HuggingFace, TFHub) for Natural Language Processing tasks (Natural Language Inference, Question-Answering etc.) with open-source corpora (SQUAD, MNLI, etc.); Generative models (OpenAI – GPT - X) and Encoder based models (BERT, RoBERTa, DistilBERT) for solving language-based reasoning problems; Computational semantics tools (WordNet, SpaCy, NLTK) for linguistic analysis; Advanced statistical and modelling methods (e.g., graphical models, Bayesian inference, neural networks, SVM, Random Forest etc.) using scikit-learn, scipy; Model Assessment and Validation: testing, tuning, and validation techniques (Chi square, ROC curve, root mean square error etc.); Performing trend, sentiments and cluster analysis on data to answer practical business problems and provide recommendations, key insights to business (Embeddings: Word2Vec, TFIDF) (Clustering Algorithms, KMeans, hierarchical Clustering) (Dimensionality Reduction (PCA, FAMD); Conducting exploratory data analysis activities using Pandas, Numpy, Matplotlib, Plotly; CI/CD, testing, and documentation in software development (UML, State and Activity workflows, Astah, Java). Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills. Rate of pay: $110,302.00 - 180,000.00/year. Additional compensation includes annual or quarterly performance incentives.
Job Location: 811 Excellence Dr, Bentonville, AR 72716 Duties: Design and deploy intelligent, goal-driven agents to optimize customer delivery promises, fulfillment routing, and root-cause-analysis across end-to-end and supply chain workflows. Build agents capable of reasoning, planning, tool usage, and memory management (short/long-term memory) using frameworks such as LangChain, LangGraph, and Google ADK (Agent Development Kit), Pydantic. Leverage state-of-the-art LLMs (GPT, Claude, Gemini), and implementing trainable model architectures (leveraging Huggingface, PyTorch, Tensorflow) to build sophisticated NLP solutions, including context engineering, chain-of-thought reasoning, and tool calling. Deployment of AI/ML and Agentic systems into production environments. Utilize Docker, Kubernetes, cloud platforms (GCP/Azure) and Airflow to ensure scalability, reliability, and low latency, with robust CI/CD pipelines for continuous improvement. Build scalable Retrieval-Augmented Generation (RAG) systems to enable real-time access to logistics policies, SOPs, and network constraints. Manage vector databases (Pinecone, Milvus, ChromaDB) and knowledge graphs to improve decision accuracy in fulfillment, routing, and issue resolution. Apply classical and advanced machine learning techniques (XGBoost, K-Means Clustering, Regression, SVMs, Random Forest etc.) on large-scale structured and unstructured datasets to drive improvements delivery ETA prediction and reliability. Use Python ecosystems (Pandas, NumPy, Scikit-learn) for scalable data processing and modeling. Build and optimize workflows using PostgreSQL for transactional systems and Google BigQuery for large-scale analytics, ensuring data quality, consistency, and performance at Walmart scale. Develop evaluation and observability frameworks using tools like Arize Phoenix and LangFuse to measure model and agent performance in production, accuracy of decisions, hallucination rates, latency, and cost. Continuously translate advancements from leading AI research avenues (NeurIPS, ICML, ICLR, ACL, EMNLP etc.) into scalable enterprise solutions that can be productionized to improve end to end supply chain. Minimum education and experience required: Bachelor’s degree or the equivalent in Computer Science, Analytics, Engineering (any), or related field plus 1 years of experience in analytics or a related field; OR Master’s degree or the equivalent in Computer Science, Analytics, Engineering (any), or related field.
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 29, 2026 · 1 day ago
- Recorded sightings
- 3
- Last seen by us
- Oct 31, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
What you'll do...
Position: Senior Data Scientist – Supply Chain Optimization
Job Location: 811 Excellence Dr, Bentonville, AR 72716
Duties: Design and deploy intelligent, goal-driven agents to optimize customer delivery promises, fulfillment routing, and root-cause-analysis across end-to-end and supply chain workflows. Build agents capable of reasoning, planning, tool usage, and memory management (short/long-term memory) using frameworks such as LangChain, LangGraph, and Google ADK (Agent Development Kit), Pydantic. Leverage state-of-the-art LLMs (GPT, Claude, Gemini), and implementing trainable model architectures (leveraging Huggingface, PyTorch, Tensorflow) to build sophisticated NLP solutions, including context engineering, chain-of-thought reasoning, and tool calling. Deployment of AI/ML and Agentic systems into production environments. Utilize Docker, Kubernetes, cloud platforms (GCP/Azure) and Airflow to ensure scalability, reliability, and low latency, with robust CI/CD pipelines for continuous improvement. Build scalable Retrieval-Augmented Generation (RAG) systems to enable real-time access to logistics policies, SOPs, and network constraints. Manage vector databases (Pinecone, Milvus, ChromaDB) and knowledge graphs to improve decision accuracy in fulfillment, routing, and issue resolution. Apply classical and advanced machine learning techniques (XGBoost, K-Means Clustering, Regression, SVMs, Random Forest etc.) on large-scale structured and unstructured datasets to drive improvements delivery ETA prediction and reliability. Use Python ecosystems (Pandas, NumPy, Scikit-learn) for scalable data processing and modeling. Build and optimize workflows using PostgreSQL for transactional systems and Google BigQuery for large-scale analytics, ensuring data quality, consistency, and performance at Walmart scale. Develop evaluation and observability frameworks using tools like Arize Phoenix and LangFuse to measure model and agent performance in production, accuracy of decisions, hallucination rates, latency, and cost. Continuously translate advancements from leading AI research avenues (NeurIPS, ICML, ICLR, ACL, EMNLP etc.) into scalable enterprise solutions that can be productionized to improve end to end supply chain.
Minimum education and experience required: Bachelor’s degree or the equivalent in Computer Science, Analytics, Engineering (any), or related field plus 1 years of experience in analytics or a related field; OR Master’s degree or the equivalent in Computer Science, Analytics, Engineering (any), or related field.
Skills Required: Must have experience with: Building Deep Learning Model Architectures in Python using PyTorch, TensorFlow and Langchain; Pre-training/Fine-tuning language models (from HuggingFace, TFHub) for Natural Language Processing tasks (Natural Language Inference, Question-Answering etc.) with open-source corpora (SQUAD, MNLI, etc.); Generative models (OpenAI – GPT - X) and Encoder based models (BERT, RoBERTa, DistilBERT) for solving language-based reasoning problems; Computational semantics tools (WordNet, SpaCy, NLTK) for linguistic analysis; Advanced statistical and modelling methods (e.g., graphical models, Bayesian inference, neural networks, SVM, Random Forest etc.) using scikit-learn, scipy; Model Assessment and Validation: testing, tuning, and validation techniques (Chi square, ROC curve, root mean square error etc.); Performing trend, sentiments and cluster analysis on data to answer practical business problems and provide recommendations, key insights to business (Embeddings: Word2Vec, TFIDF) (Clustering Algorithms, KMeans, hierarchical Clustering) (Dimensionality Reduction (PCA, FAMD); Conducting exploratory data analysis activities using Pandas, Numpy, Matplotlib, Plotly; CI/CD, testing, and documentation in software development (UML, State and Activity workflows, Astah, Java). Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills.
Rate of pay: $110,302.00 - 180,000.00/year. Additional compensation includes annual or quarterly performance incentives.
Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.com.
Wal-Mart is an Equal Opportunity Employer.
Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.Source details
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- Pay
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- Location & working pattern
Bentonville, AR
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