(USA) Data Scientist III

Walmart

Quick summary

Work type: On-site
Location: Bentonville, AR · Sunnyvale, CA
Salary: $90,000–$180,000 / yr
Posted: 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $151k

This role $135k

$78k most similar roles pay here $202k

This role pays less than 57% of similar roles. Most pay $126,800–$175,500 — the shaded band above. At the midpoint, this role pays about $135k versus about $151k 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 499 open roles on FindRole.

Listed pay typically runs $117,000–$234,000 across 493 roles with salary data.

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View all roles at Walmart

At a glance

TL;DR · (USA) Data Scientist III

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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 day-to-day involves 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’ll need 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 business growth by integrating data-driven insights across categories such as groceries and entertainment, driving operational efficiency at scale.

Skills

Python PyTorch TensorFlow Keras Scikit-learn statsmodels SQL Temporal Fusion Transformers N-BEATS PATCHTST Generative AI Large-scale neural networks Automated batch pipelines Cloud platforms GPU-based model training Time series forecasting Deep learning Optimization theory Attention-based architectures Transformer-based neural networks

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 for enhanced model training pipelines.
Design 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.

What we're looking for

Proficient in Python, SQL, and deep learning frameworks like PyTorch, TensorFlow/Keras.
Strong foundation in time series forecasting, deep learning, and optimization theory.
Experience with transformer-based neural networks for real-world applications.
Ability to design and train large-scale neural networks for various analytical tasks.
Expertise in building production-ready cloud applications integrated with internal systems.
Demonstrated proficiency in GPU-based model training pipelines and managing experiments at scale.

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