below marketmost similar roles pay hereabove market
This role pays more than
87%
of similar roles. Most pay
$162,000–$214,500
— the blue band above.
At the midpoint, this role pays about
$214k
versus about
$188k
for comparable roles.
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
on FindRole.
Listed pay typically runs
$121,000–$242,000
across 473 roles with salary data.
JOB TITLE: (USA) Principal, Data Scientist
The (USA) Principal, Data Scientist joins the Marketplace data science team to build machine learning products for a third-party seller gateway. This role involves consulting with business stakeholders to develop algorithm-based recommendations, guiding other data scientists across sub-domains, and driving ML Ops best practices. You will lead complex projects from conception to production, translating business requirements into technical strategies for areas like fraud prevention, forecasting, inventory management, and price optimization. Key technologies include Python, R, Py Spark, Google Cloud Platform, Vertex AI, Kubeflow, and Hadoop. You will utilize advanced techniques such as NLP, graph ML, causal inference, and Gen-AI, including vector databases and LLM gateways. The work focuses on creating scalable, robust technical solutions to improve the marketplace experience for sellers and customers.
What does a Data Scientist earn in California?
Median $214500 from 114 postings across 26 companies.
Translate business requirements into technical strategies and initiatives aligned with company objectives.
Lead the end-to-end development, scaling, and deployment of complex machine learning products.
Guide data scientists across multiple sub-domains to ensure on-time delivery of ML solutions.
Identify complex business problems and opportunities solvable through advanced machine learning techniques.
Define key metrics and quantify the business impact of all deployed ML products.
Drive efficiency in ML Ops practices, resource utilization, and algorithmic innovation across the domain.
Consult with business stakeholders to develop algorithm-based recommendations into actionable business plans.
Review model evaluation metrics and ensure all testing information is documented and maintained.
What we're looking for
Must have a Bachelor's degree in a related field and 5 years of analytics experience, a Master's and 3 years, or 7 years of experience without a degree.
Must have 10-15 years of relevant experience with at least 10 years specifically as a data science technical lead.
Must have a degree in Computer Science, Statistics, Mathematics, or a related area.
Must have deep experience building data science solutions in areas like fraud prevention, forecasting, inventory management, and price optimization.
Must have strong experience in machine learning including classification, regression, NLP, forecasting, optimization, graph ML, and causal inference.
Must have strong experience with Python, Py Spark, Google Cloud Platform, Vertex AI, Kubeflow, and big data platforms like Hadoop.
Must have experience with GPU/CUDA for computational efficiency.
Must have experience in Gen-AI including embedding generation, vector databases, LLM gateways, and RAG-based agents (preferred).
GenAI
LLMs
Python
Machine Learning
Deep Learning
Spark
Hive
GCP
Azure
CI/CD
TensorFlow
scikit learn
Distributed Systems
ML Pipelines
Natural Language Processing
Scala
R
Python
SQL
Spark
Scala
R
Hadoop
Hive
Map Reduce
TensorFlow
scikit learn
NLP
Computer Vision
Gen AI
Agentic AI
Git
Data Warehouse
Statistics
Machine Learning
Deep Learning