below marketmost similar roles pay hereabove market
This role pays more than
88%
of similar roles. Most pay
$165,000–$214,500
— the blue band above.
At the midpoint, this role pays about
$214k
versus about
$190k
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
719 open roles
on FindRole.
Listed pay typically runs
$117,000–$234,000
across 592 roles with salary data.
JOB TITLE: (USA) Principal, Data Scientist
The Principal Data Scientist joins the personalization marketing data science team to lead advanced initiatives across digital marketing channels like SEM, SEO, CRM, Display, and Paid Social. This role involves developing and deploying innovative machine learning models, designing rigorous experiments, and building predictive personalization models to improve customer engagement. You will architect experimentation platforms, establish reusable modeling frameworks, and manage feature pipelines while mentoring team members on coding and methodology. The position requires proficiency in Python, SQL, and MLOps practices, along with experience in deep learning and statistical analysis. You will solve complex business problems by analyzing extensive omni-channel commerce data to optimize marketing effectiveness, generate high-quality demand, and deliver actionable insights through scalable, data-driven solutions and causal measurement frameworks.
What does a Data Scientist earn in California?
Median $214500 from 134 postings across 32 companies.
Develop and deploy advanced AI, machine learning, and statistical solutions for marketing science and personalization.
Define scalable data science strategies that align with specific business objectives.
Design rigorous experiments, causal measurement frameworks, and incrementality analyses.
Architect experimentation platforms for audience assignment, metrics, analysis, and reporting.
Build predictive and personalization models to improve customer engagement and marketing performance.
Establish reusable modeling frameworks, feature pipelines, and model lifecycle standards.
Mentor data scientists on methodology, coding, experimentation, and communication best practices.
What we're looking for
Must have a Bachelor's degree in a related field and 5 years of analytics experience, a Master's degree and 3 years of experience, or 7 years of experience.
Must have 5+ years of experience in machine learning, deep learning, and advanced statistical analysis.
Must be proficient in programming languages including Python and SQL for code development, testing, and automation.
Must have strong knowledge of MLOps practices for model lifecycle management and scalability in production environments.
Must have expertise in data quality assessment, feature engineering, and experimentation to drive data-driven solutions.
Must have experience with cloud platforms for model deployment and management.
Must have proven leadership skills to mentor teams and guide technical problem formulation and solution delivery.
Preferred: PhD in a related field, publications/peer review experience, and successful completion of assessments in Python, Spark, Scala, or R.
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