Minimum education and experience required: Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Data Analytics, or related field and 1 year of experience in an analytics related field; OR Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Data Analytics, or related field and 3 years of experience in an analytics related field.
Skills required: Experience in scalable data analytics, statistical modeling, data visualization, feature engineering on various data (PowerBI, Tableau, Pandas, NumPy, SciPy, Spark, PySpark). Experience with AI Model Pre-training, including designing distributed training pipelines and large-scale data curation, and optimizing foundational architectures using PyTorch, DeepSpeed (ZeRO), and Hugging Face. Experience with AI Model Post-training & Human Alignment, including implementing supervised fine-tuning (SFT), RLHF (Reinforcement Learning from Human Feedback), and early Transfer Learning for domain-specific optimization. Experience with Deep Learning and Computer Vision, including building and optimizing image classification and feature extraction pipelines using EfficientNet, ResNet, and TensorFlow. Experience with Distributed Data Processing and large-scale data engineering in SQL/NoSQL environments, including query optimization in Hive, BigQuery, and Spark. Experience with Natural Language Processing (NLP): Text classification and sentiment analysis using BERT, RoBERTa, and Transformer architectures. Experience with Information Retrieval, including utilizing Vector Embeddings, Cosine Similarity, and FAISS for high-dimensional semantic search. Experience processing distributed data at scale using SQL and NoSQL environments, including query optimization and data lake management in Hive and BigQuery. Experience with Computer Vision techniques, including implementing YOLO or Mask R-CNN for Object Detection, Instance Segmentation, and Image Enhancement. Experience with cloud-based model training and inference, leveraging managed services in Azure (ML Studio) and GCP (Vertex AI) for lifecycle management. Experience with Project Version Control and collaborative software development lifecycle (SDLC) management using Git, GitHub, and CI/CD pipelines. Experience evaluating model performance using robust statistical indexes including F1-score, ROC-AUC, mAP, and conducting A/B testing for model comparison. Experience with Web Crawling and ETL techniques, utilizing BeautifulSoup or Scrapy to pull and structure data from internal and external catalogs. Employer will accept any amount of graduate coursework, graduate research experience or professional experience with the required skills.
Salary Range: $168,917/year to $234,000/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.
