Senior Data Scientist

Walmart • Sunnyvale, CA

6d • $168,917 - $234,000 • Onsite

About The Position

The Senior Data Scientist develops custom data models and algorithms to support business solutions for Walmart eCommerce. The role builds complex datasets from internal and external sources; conducts advanced statistical analysis to identify trends and significant relationships; and develops learning systems to analyze continuous data flows and offline data. It trains, validates, and scales algorithms for large datasets and combines data features to develop search models and predict future data characteristics. The position also researches industry techniques and trends, develops models of current-state processes to identify improvements, and works with cross-functional business partners and project teams to provide analytical support.

The role uses statistical, machine-learning, data-engineering, computer-vision, NLP, and information-retrieval methods. It involves designing and optimizing AI model pre-training and post-training workflows, distributed training pipelines, data curation, human-alignment techniques, and cloud-based model training and inference. The position evaluates model performance using statistical metrics and A/B testing, and uses version control and collaborative software-development practices.

The position is located at 1375 Crossman Avenue, Sunnyvale, CA 94089. The stated salary range is $168,917 to $234,000 per year, with additional annual or quarterly performance incentives.

Requirements

• Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Data Analytics, or a related field and 1 year of experience in an analytics-related field; or a bachelor’s degree in one of those fields and 3 years of experience in an analytics-related field.
• Experience in scalable data analytics, statistical modeling, data visualization, and feature engineering using tools such as PowerBI, Tableau, Pandas, NumPy, SciPy, Spark, or PySpark.
• Experience with AI model pre-training, distributed training pipelines, large-scale data curation, and optimizing foundational architectures using PyTorch, DeepSpeed (ZeRO), and Hugging Face.
• Experience with AI model post-training and human alignment, including supervised fine-tuning (SFT), RLHF, and transfer learning for domain-specific optimization.
• Experience with deep learning and computer vision, including 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 NLP, including text classification and sentiment analysis using BERT, RoBERTa, and Transformer architectures.
• Experience with information retrieval using 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 implementing computer-vision techniques such as YOLO or Mask R-CNN for object detection, instance segmentation, and image enhancement.
• Experience with cloud-based model training and inference using Azure ML Studio and GCP Vertex AI.
• Experience with Git, GitHub, and CI/CD pipelines for version control and collaborative software development lifecycle management.
• Experience evaluating model performance using F1-score, ROC-AUC, and mAP, and conducting A/B testing for model comparison.
• Experience with web crawling and ETL using BeautifulSoup or Scrapy to collect and structure data from internal and external catalogs.
• The employer will accept any amount of graduate coursework, graduate research experience, or professional experience with the required skills.

Responsibilities

• Develop custom data models and algorithms to drive business solutions.
• Build complex datasets from multiple internal and external data sources.
• Conduct advanced statistical analysis to identify trends and significant data relationships.
• Build learning systems to analyze continuous data flows and perform offline data analysis.
• Train algorithms to apply models to new datasets; validate models and algorithmic techniques; and scale algorithms to large datasets.
• Combine data features to develop search models and predict future data characteristics and search results.
• Research industry techniques, best practices, and trends, and apply up-to-date technology to assigned projects.
• Analyze large datasets and provide analytical support to Walmart eCommerce project teams.
• Work with cross-functional business partners.
• Develop models of the current state to determine needed improvements.
• Design distributed model-training pipelines and curate large-scale datasets for AI model pre-training.
• Implement supervised fine-tuning, RLHF, and transfer learning for domain-specific model optimization.
• Build and optimize deep-learning and computer-vision pipelines, including image classification, feature extraction, object detection, instance segmentation, and image enhancement.
• Process distributed data at scale in SQL and NoSQL environments, including query optimization and data-lake management.
• Develop NLP applications such as text classification and sentiment analysis, and information-retrieval systems using vector embeddings and semantic search.
• Use cloud-based services for model training, inference, and lifecycle management.
• Manage collaborative software development using version control and CI/CD pipelines.
• Evaluate model performance using statistical indexes and conduct A/B testing.
• Use web crawling and ETL techniques to collect and structure data from internal and external catalogs.

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, 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