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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
on FindRole.
Listed pay typically runs
$121,000–$242,000
across 473 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 seller operations, including onboarding, catalogs, and order fulfillment. This role involves owning the MLOps lifecycle, developing scalable end-to-end data science solutions, and building infrastructure like Kafka pipelines for unified logging and monitoring. You will apply SRE principles to ML workloads, optimize cloud deployments, and lead code quality through reviews and mentoring. Key responsibilities include building distributed training and inference pipelines and enhancing data feedback workflows. Required skills include Python, SQL, and big data platforms like Hadoop, Hive, Pig, Map Reduce, and Spark. You must possess strong knowledge of machine learning foundations, statistics, supervised and unsupervised learning, and deep learning to solve complex marketplace problems.
What does a Data Scientist earn in Washington?
Median $212000 from 33 postings across 16 companies.
Build scalable end-to-end data science solutions and machine learning products for Walmart Marketplace.
Own the MLOps lifecycle, including data monitoring, code refactoring, and model lifecycle management.
Develop and maintain scalable MLOps infrastructure, such as Kafka pipelines for unified logging.
Apply SRE principles to optimize cloud deployments and troubleshoot application latency for ML workloads.
Build continuous, distributed training, inference, and performance monitoring pipelines for 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.
Consult with stakeholders to align AI solutions with business objectives and deploy holistic ML models.
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 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 experience with SQL and relational databases, data warehouses, and Git.
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.
Python
Machine Learning
Spark
Scala
R
TensorFlow
scikit learn
Tableau
Matplotlib
Plotly
Big Data
Data Visualization
Predictive Analytics
Data Governance
Cloud-native Architecture
Statistics
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