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$162,000–$214,500.
Based on 240 similar postings.
Employer
About Walmart
Walmart Inc. is the world''s largest retailer by revenue, operating a chain of hypermarkets, discount department stores, and grocery stores, as well as a growing e-commerce presence through Walmart.com. Industry: General Merchandise & Grocery Retail
Walmart currently has
825 open roles
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Listed pay typically runs
$121,000–$242,000
across 473 roles with salary data.
The (USA) Staff, Data Scientist joins the BuyBox Data Science team within the Search & Personalization organization. In this role, you will lead advanced machine learning solutions for BuyBox offer ranking, Variant Leader Selection, Search, and Personalization. You will build and advance ranking and recommendation systems using Learning-to-Rank, deep learning, and modern ML techniques. Your daily work involves applying Generative AI, LLMs, and neural networks to improve semantic understanding and customer experience. You will manage projects from problem definition through offline evaluation, A/B testing, and production deployment. Key technologies include Python, BigQuery, PySpark, Hive, and data visualization tools. You will solve complex problems at the intersection of Search, Recommendation Systems, Marketplace, and eCommerce to determine the best offers and most relevant product variants for customers.
What does a Data Scientist earn in California?
Median $214500 from 114 postings across 26 companies.
Develop and lead advanced ML solutions for BuyBox offer ranking, Search, and Personalization systems.
Build ranking and recommendation systems using Learning-to-Rank, deep learning, and modern ML techniques.
Apply Generative AI, LLMs, and neural networks to improve semantic understanding and customer experience.
Lead projects from initial problem definition and modeling through offline evaluation and A/B testing.
Deploy and monitor scalable ML models in production environments to ensure high performance.
Establish ML best practices and provide technical leadership and mentorship to other Data Scientists.
Partner with Product and Engineering stakeholders to define technical roadmaps and business strategies.
What we're looking for
Meet one of three education/experience paths: Bachelor's with 4 years analytics experience, Master's with 2 years analytics experience, or 6 years of analytics experience.
Demonstrate proven expertise in machine learning, ranking, recommendation systems, information retrieval, and personalization.
Exhibit proficiency in Python, BigQuery, PySpark, Hive, and data visualization tools.
Possess a deep understanding of Learning-to-Rank, neural networks, embeddings, representation learning, and modern recommendation techniques.
Experience applying Generative AI and LLMs to real-world machine learning problems.
Experience building and deploying data pipelines, MLOps, and large-scale production ML systems.
Maintain strong knowledge of experimentation, A/B testing, statistical methods, and model evaluation.
Possess a PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics (preferred).
Machine Learning
Generative AI
Large Language Models
LLMs
Python
Spark
Scala
R
TensorFlow
scikit learn
MLOps
Vector Search
Embeddings
Transformer Models
Information Retrieval
Recommendation Systems
Distributed Model Deployment
Causal Inference
WCAG) 2.2 AA
Generative AI
Large Language Models
MLOps
Python
Spark
Scala
R
TensorFlow
scikit learn
Transformer Models
Vector Search
Embeddings
Information Retrieval
Recommendation Systems
Causal Inference
Distributed Model Deployment
Data Visualization
Statistics
Generative AI
Large Language Models
LLMs
MLOps
Python
Spark
Scala
R
TensorFlow
scikit learn
transformer models
vector search
Embeddings
Information Retrieval
Recommendation Systems
causal inference
distributed model deployment
semantic search
Optimization Models