Senior, Data Scientist

Walmart

Hybrid

Quick summary

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

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $156k
This role $135k
$74k most similar roles pay here $236k

This role pays less than 65% of similar roles. Most pay $126,800–$185,527 — 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 529 open roles on FindRole.

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

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View all roles at Walmart

At a glance

TL;DR · Senior, Data Scientist

We are seeking a Senior Data Scientist to join Sam’s Club's 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 emerging fraud trends, and building high-dimensional real-time ML models to prevent fraud in areas like E-Commerce, In-club payment fraud, return abuse, and account takeover. You will 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 5-7 years of experience in building production machine learning systems, proficiency in Python and SQL, and hands-on experience with distributed computing tools like PySpark/GCP/BigQuery, as well as familiarity with GNNs and Generative AI for decision intelligence and explainability.

What you'll do

  • Develop machine learning models for detecting fraud across E-Commerce and In-club payment fraud.
  • Design graph-based systems using GNNs to detect coordinated fraud rings and network-level risks.
  • Enhance fraud detection with Generative AI techniques, automating investigations and improving model explainability.
  • Work on scalable ML models in big data mining, graph modeling, and other domains.
  • Collaborate with engineering teams to implement and deploy machine learning pipelines at scale.

What we're looking for

  • 5+ years of experience building production machine learning systems at scale.
  • Proficiency in Python and SQL for data manipulation and analysis.
  • Experience with large datasets and distributed computing tools like PySpark/GCP/BigQuery.
  • Hands-on experience with Graph Neural Networks (GNNs) and graph embeddings.
  • Familiarity with Generative AI techniques, including LLM-based approaches for explainability.
  • Strong collaboration skills to work effectively with cross-functional teams.

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