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Senior, Data Scientist
WalmartUnited Statesfull_timeVerifiedPosted 30 Jan 2026
💰 $234,000/yr($117,000/yr – $234,000/yr)
About the role
Position Summary...
What you'll do...
We are looking for a Senior Data Scientist to join our science team and build state of the art solutions to detect, prevent, and mitigate fraud across Walmart’s multiple international markets. Our mission is to protect customers, sellers, and the business by enabling safe, trusted, and seamless commerce throughout the online shopping journey. We develop powerful AI and ML driven systems to address highly complex, real world fraud problems at scale. In this role, you will work on industry defining challenges and push the boundaries of fraud detection and prevention by advancing areas such as machine learning, applied statistics, graph and network analysis, optimization, anomaly detection, NLP, and large scale, customer and platform facing system design.What you will do
- Partner with data scientists, engineers, and product managers to design, train, test, and deploy machine learning models that prevent and mitigate fraud across multiple international markets.
- Work on problem spaces with high ambiguity and translate business, risk, and engineering requirements into a clear roadmap for delivering fraud detection and prevention solutions.
- Design and evaluate models that mathematically express and solve complex fraud problems with limited historical precedent or evolving adversarial behavior.
- Perform rigorous offline analysis and controlled A/B testing, and communicate results and tradeoffs to both technical and non technical stakeholders through clear verbal and written communication.
- Apply and adapt cutting edge academic research and industry best practices to develop novel approaches for fraud detection, risk scoring, anomaly detection, and abuse prevention.
- Own models post deployment by monitoring performance, retraining as needed, and continuously improving them within a highly scalable, production grade infrastructure.
- Publish meaningful research findings internally and externally, contribute to conferences and journals where appropriate, and file patent applications for novel fraud solutions.
What you will bring
- MS or PhD in a relevant technical field such as Computer Science, Machine Learning, Applied Mathematics, Statistics, Operations Research, or Engineering, with at least 4 years of relevant industry or applied research experience.
- Strong foundation in machine learning, deep learning, optimization, algorithms, applied statistics, and software development, with proven ability to apply these skills to real world fraud problems.
- Experience or strong interest in areas such as fraud detection, risk modeling, anomaly detection, graph and network analysis, and adversarial modeling.
- Proficiency in Python, SQL, PySpark, machine learning libraries, and large scale data processing systems in a cloud based environment.
- Experience publishing in peer reviewed conferences or journals, or demonstrated ability to translate advanced research into production ready systems.
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