Data Scientist III

Walmart

Hybrid

Quick summary

Work type
Hybrid
Location
Bentonville, AR
Salary
$90,000–$180,000 / yr
Posted
5 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $157k
This role $135k
$74k most similar roles pay here $236k

This role pays less than 64% of similar roles. Most pay $126,800–$187,531 — the shaded band above. At the midpoint, this role pays about $135k versus about $157k 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 529 open roles on FindRole.

Listed pay typically runs $117,000–$234,000 across 523 roles with salary data.

Most-posted roles

View all roles at Walmart

At a glance

TL;DR · Data Scientist III

Join Sam’s Club as a Data Scientist III on the fraud detection team, where you will own fraud risks across various product segments and collaborate closely with product managers, engineers, and business stakeholders. Your responsibilities include setting strategic goals, detecting changing fraud trends, and building high-dimensional real-time ML models to prevent fraud in areas like E-Commerce, In-club payment, returns, and account takeovers. You’ll leverage Graph Neural Networks (GNNs) and Generative AI techniques to enhance detection accuracy and automate investigations, while also working on scalable ML models and deploying them at scale with engineering teams. The ideal candidate has 3-5 years of experience in building production machine learning systems, proficiency in Python, SQL, PySpark/GCP/BigQuery, and hands-on knowledge of GNNs and Generative AI for decision intelligence.

What you'll do

  • Develop machine learning models for detecting fraud across E-Commerce and In-club payment areas.
  • Design graph-based systems using GNNs to identify coordinated fraud rings and network-level risks.
  • Enhance fraud detection with Generative AI techniques, automating workflows and improving model explainability.
  • Collaborate with stakeholders to translate business problems into data science solutions for fraud prevention.
  • Implement scalable ML models and algorithms in big data mining and graph modeling domains.

What we're looking for

  • 3-5 years of experience building production machine learning systems at scale.
  • Proficiency in Python and SQL for data manipulation and insight extraction from large datasets.
  • Hands-on experience with distributed computing tools like PySpark, GCP, or BigQuery.
  • Expertise in Graph Neural Networks (GNNs), graph embeddings, and large-scale graph processing frameworks.
  • Experience applying Generative AI techniques for decision intelligence and workflow automation.
  • Strong collaboration skills to work effectively with cross-functional teams on fraud risk solutions.

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