Role Overview:
As the Distinguished Data Scientist, you will bridge hands-on fraud data science & modeling, ML research, and governance across our fraud technology stack. You'll shape our strategy for cutting-edge fraud detection while ensuring rigorous model lifecycle practices and oversight. This role plays a critical function in making our fraud defenses both intelligent and responsible, while staying on the frontier of research-driven innovation.
Key Responsibilities:
Modeling & Production ML
· Lead the design and delivery of high-performance ML models across fraud use cases like identity verification, payment risk, returns abuse, and synthetic accounts.
· Develop hybrid decision-making systems that combine ML predictions with business logic and rules for improved precision and control.
· Ensure models are production-ready, optimized for both batch and real-time inference environments.
· Partner with engineers to define feature pipelines, scoring interfaces, and data contracts.
ML Research & Innovation
· Explore and prototype advanced ML techniques: semi-supervised learning, agentic AI, continual learning, anomaly detection.
· Collaborate with enterprise ML/AI research teams to apply foundational innovations to real-world fraud problems.
· Identify and validate new fraud signals and data sources to increase risk detection coverage.
ML Governance & Controls
· Establish governance frameworks for fairness, explainability, documentation, alerting, and drift detection.
· Build and maintain dashboards and SQL-based analytics for monitoring model health and emerging anomalies.
· Lead responsible AI practices and advise cross-functional pods on model risk management.
Cross-Functional Leadership
· Serve as the technical expert and decision-maker for modeling in pod-based execution teams.
· Collaborate with Solutions Engineering to integrate model outputs into APIs, tools, and workflows.
· Partner with Platform & Tools to ensure infrastructure supports agile modeling, experimentation, and retraining.
· Guide QA and release validation for ML components and outputs.
Mentorship & Thought Leadership
· Mentor senior data scientists, researchers, and analysts across modeling and governance.
· Lead initiatives to standardize model experimentation, evaluation, documentation, and deployment.
· Represent fraud technology in enterprise-wide forums for responsible AI and risk governance.
Qualifications:
You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable.
For information about PTO, see .
Live Better U is a Walmart-paid education benefit program for full-time and part-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short-form certificates. Tuition, books, and fees are completely paid for by Walmart.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart .
The annual salary range for this position is $169,000.00-$338,000.00
Additional compensation includes annual or quarterly performance bonuses.
Additional compensation for certain positions may also include:
- Stock
Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.
Option 1: Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field. Option 2: Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 3: 8 years' experience in an analytics or related field.Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.
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