(USA) Data Scientist III

Walmart

Quick summary

Work type: On-site
Location: Bentonville, ARSunnyvale, CA
Salary: $90,000–$180,000 / yr
Posted: 12 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $156k

This role $135k

$77k most similar roles pay here $210k

This role pays less than 59% of similar roles. Most pay $126,800–$184,900 — the shaded band above. At the midpoint, this role pays about $135k versus about $156k 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 188 open roles on FindRole.

Listed pay typically runs $110,000–$220,000 across 182 roles with salary data.

Most-posted roles

View all roles at Walmart

At a glance

TL;DR · (USA) Data Scientist III

Apply Now Log in to save

As a Data Scientist at Walmart’s dynamic team focused on enhancing customer experiences through technological innovation across retail and eCommerce, you will develop scalable time series forecasting systems using advanced models like Temporal Fusion Transformers and N-BEATS. Your daily tasks include applying generative AI to synthesize data for model training, designing large-scale neural networks for anomaly detection, and deploying these solutions via automated batch pipelines on cloud platforms. You must have a strong foundation in deep learning, time series forecasting, and optimization theory, along with proficiency in Python, SQL, PyTorch, TensorFlow/Keras, Scikit-learn, and statsmodels. This role supports Walmart’s U.S. stores and eCommerce by driving operational efficiency through data-driven insights and scalable solutions.

Skills

Python PyTorch TensorFlow Keras Scikit-learn statsmodels SQL Temporal Fusion Transformers N-BEATS PATCHTST generative AI NLP-based assistants large-scale neural networks automated batch pipelines cloud platforms GPU-based model training pipelines time series forecasting deep learning optimization theory

What you'll do

Develop scalable time series forecasting systems using advanced models like Temporal Fusion Transformers and N-BEATS.
Apply generative AI to synthesize time series data and build intelligent NLP-based assistants for analytics enablement.
Design and train large-scale neural networks for anomaly detection, causal inference, and deployment via automated batch pipelines.
Build production-ready applications on cloud platforms, integrated with internal systems for scalable insights delivery.
Mentor team members and ensure alignment with data governance and quality standards in a dynamic environment.

What we're looking for

Proficiency in time series forecasting and deep learning with sequence modeling expertise.
Experience training and deploying transformer-based neural networks for real-world applications.
Strong coding skills in Python, SQL, PyTorch, TensorFlow/Keras, Scikit-learn, and statsmodels.
Ability to work on GPU-based model training pipelines and manage large-scale experiments.
Demonstrated success in building production-ready cloud applications integrated with internal systems.
Expertise in developing scalable time series forecasting systems using advanced models like TFT, N-BEATS.

Save