STAFF, DATA SCIENTIST

About Team
The International Data Science team at Walmart Global Tech is focused on using the latest research in machine learning, statistics, and optimization to solve complex business problems across assortment, pricing, sourcing, customer, supply chain, and replenishment for multiple countries within Walmart s global operations.As part of this mission, the Anti-Fraud Data Science group builds real-time fraud detection and prevention systems to protect Walmart s customers, associates, and business from evolving fraud threats. We leverage advanced machine learning, graph analytics, anomaly detection, and generative AI to detect and mitigate fraud at scale, ensuring trust and security across Walmart s global ecosystem.

Your Opportunity

As a Staff Data Scientist in Fraud, you will:

• Design and implement advanced ML algorithms for real-time fraud detection, including graph-based models, anomaly detection, and behavioral modeling.
• Develop adaptive risk-scoring frameworks that evolve with new fraud patterns.
• Prototype novel algorithms and scale them into production-ready, low-latency systems.
• Leverage LLMs and agent-based architectures for automated fraud intelligence and dynamic rule generation.
• Collaborate with engineering teams to integrate models into streaming pipelines (Spark) for real-time decisioning.
• Continuously monitor and optimize models using A/B testing, causal inference, and feedback loops.

What You will do

• Translate complex fraud patterns into ML-driven solutions with measurable business impact.
• Lead multiple fraud-focused ML products, ensuring scientific rigor and production readiness.
• Define KPIs for fraud systems (precision, recall, latency, false positive rate) and optimize for trade-offs.
• Drive innovation in graph ML, adversarial detection, and generative AI for fraud intelligence.
• Ensure explainability, compliance, and governance for all deployed models.
• Mentor data scientists in advanced modeling and scalable ML practices.

Our Ideal Candidate

• Strong foundation in machine learning theory, statistical modeling, and algorithm design.
• Expertise in graph ML, anomaly detection, and rare-event modeling.
• Experience with real-time ML systems and streaming architectures.
• Familiarity with LLMs, RAG, and agent-based systems for fraud investigation.
• Ability to bridge research and engineering to deliver production-grade solutions.

What You will Bring

• Master s (>8 years) or Ph.D. (>5 years) in Computer Science, Statistics, Applied Mathematics, or related field.
• Proven experience in:
  • Anomaly detection, graph-based algorithms, and behavioral modeling.
  • Real-time scoring systems and low-latency ML deployment.
  • Generative AI and LLM integration for fraud intelligence.
  • Big data platforms (Hadoop, Spark), Python, PyTorch/TensorFlow.
• Familiarity with cloud platforms (GCP, AWS, or Azure), Vertex AI, Kubeflow, and MLOps.

Preferred Qualifications

• Experience with device fingerprinting, identity resolution, and behavioral biometrics.
• Publications or patents in fraud detection, anomaly detection, or graph ML.
• Knowledge of adversarial ML and robust modeling techniques.
• Experience with GPU acceleration for real-time inference.

About Walmart Global Tech
Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That s what we do at Walmart Global Tech. We re a team of software engineers, data scientists, cybersecurity experts and service professionals within the world s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered.

We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.

Flexible, hybrid work
We use a hybrid way of working with primary in office presence coupled with an optimal mix of virtual presence. We use our campuses to collaborate and be together in person, as business needs require and for development and networking opportunities. This approach helps us make quicker decisions, remove location barriers across our global team, be more flexible in our personal lives.

Benefits

Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.

Belonging

We aim to create a culture where every associate feels valued for who they are, rooted in respect for the individual. Our goal is to foster a sense of belonging, to create opportunities for all our associates, customers and suppliers, and to be a Walmart for everyone.

At Walmart, our vision is "everyone included." By fostering a workplace culture where everyone is and feels included, everyone wins. Our associates and customers reflect the makeup of all 19 countries where we operate. By making Walmart a welcoming place where all people feel like they belong, we re able to engage associates, strengthen our business, improve our ability to serve customers, and support the communities where we operate.

Equal Opportunity Employer

Walmart, Inc., is an Equal Opportunities Employer By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions while being inclusive of all people.

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.