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.
As a (USA) Staff, Data Scientist, you will join the team developing foundational models for an e-commerce platform. You will design, implement, and scale high-throughput supervised fine-tuning pipelines to train foundation models for instruction following, ranking, and related tasks. Your daily work involves managing high-quality dataset mixtures, optimizing training hyperparameters like learning rate schedules, and driving model alignment toward helpfulness and safety using reinforcement learning and preference optimization. You will identify data sources, ensure data quality, and create visualizations to communicate findings. The role requires expertise in Python, PyTorch, and transformer-based architectures, alongside skills in statistical modeling, predictive analytics, and hypothesis testing. You will solve complex business challenges by translating requirements into scalable machine learning solutions for search, advertising, and personalization.
What does a Data Scientist earn in California?
Median $214500 from 134 postings across 32 companies.
Design, implement, and scale high-throughput supervised fine-tuning pipelines to train foundation models.
Optimize training hyperparameters, including learning rate schedules and other critical training configurations.
Manage high-quality dataset mixtures to improve model performance for ranking and instruction-following tasks.
Drive model alignment toward helpfulness, accuracy, and safety using preference optimization and reinforcement learning.
Identify and evaluate data sources to ensure high data quality and alignment with business requirements.
Create clear visualizations to communicate technical findings and actionable insights to stakeholders.
Deploy, monitor, and improve machine learning models within production environments.
Mentor junior team members on analytical methodologies, coding best practices, and machine learning techniques.
What we're looking for
Must have a Bachelor's degree and 4 years of analytics experience, a Master's degree and 2 years of analytics experience, or 6 years of analytics experience.
Proven expertise in data science, including predictive analytics, machine learning algorithms, statistical modeling, and hypothesis testing.
Strong programming skills in Python and experience with data visualization tools like Matplotlib, Plotly, Tableau, or Power BI.
Hands-on experience designing, training, and deploying machine learning models, specifically focusing on transformer-based architectures and large language models.
Experience optimizing large-scale training pipelines using frameworks such as PyTorch for hyperparameter tuning and high-throughput workflows.
Experience applying reinforcement learning methods (e.g., RLHF) for preference optimization, model alignment, and safety-focused applications.
Excellent verbal and written communication skills to present technical findings to both technical and non-technical stakeholders.
PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, or Econometrics (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