below marketmost similar roles pay hereabove market
This role pays more than
87%
of similar roles. Most pay
$160,102–$214,500
— the blue band above.
At the midpoint, this role pays about
$214k
versus about
$187k
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) Staff, Data Scientist
The Staff, Data Scientist joins the data science team within the Marketplace engineering organization to build machine learning products for third-party sellers. This role involves owning the MLOps lifecycle, including data monitoring, refactoring code, and building robust model monitoring workflows. You will develop scalable MLOps infrastructure, such as Kafka pipelines for unified logging, and apply SRE principles to optimize cloud deployments and troubleshoot application latency. Key responsibilities include building distributed training and inference pipelines, mentoring junior MLEs, and providing architectural guidance. Required skills include Python, SQL, and big data platforms like Hadoop, Hive, Pig, Map Reduce, and Spark. You will utilize deep learning, supervised and unsupervised learning, and statistics to solve complex problems regarding seller onboarding, catalog management, order fulfillment, and return management within the e-commerce marketplace.
What does a Data Scientist earn in California?
Median $214500 from 134 postings across 32 companies.
Build and deploy scalable end-to-end machine learning models that balance accuracy with computational efficiency.
Own the full MLOps lifecycle, including data monitoring, code refactoring, and model lifecycle management.
Develop and maintain scalable MLOps infrastructure, such as Kafka pipelines for unified logging and monitoring.
Apply SRE principles to optimize cloud deployments and troubleshoot application latency or operational issues.
Build continuous, distributed training and inference pipelines for various Marketplace initiatives.
Lead code quality and engineering best practices by conducting code reviews and mentoring junior MLEs.
Provide high-level architectural guidance and break down complex tasks to resolve project challenges.
Enhance data feedback and annotation workflows to improve the efficiency of the labeling team.
What we're looking for
Must have a Bachelor's degree in a related field and 4 years of analytics experience, a Master's degree and 2 years of experience, or 6 years of experience.
Must have very good knowledge of the foundations of machine learning and statistics.
Must have experience in machine learning, including supervised, unsupervised, and deep learning.
Must have experience analyzing complex problems and translating them into data science algorithms.
Must have experience with big data analytics to identify trends, patterns, and outliers in large volumes of data.
Must have strong experience in Python with excellent knowledge of Data Structures.
Must have strong experience with big data platforms including Hadoop, Hive, Pig, Map Reduce, Scala, and Spark.
Must have hands-on experience with Git, SQL, and relational databases or data warehouses.
Must have experience with open source frameworks such as scikit-learn, TensorFlow, or Torch (preferred).
Must have a PhD in a related field (preferred).
Must have successful completion of one or more assessments in Python, Spark, Scala, or R (preferred).
Must have knowledge of implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards (preferred).
Python
Machine Learning
Spark
Scala
R
TensorFlow
scikit learn
Tableau
Matplotlib
Plotly
Big Data
Data Visualization
Predictive Analytics
Data Governance
Cloud-native Architecture
Statistics