Position Summary...
Job Ad Description
Join Walmart's International Anti-Fraud Data Science team and help build the next generation of ecommerce fraud defenses. You'll architect real-time ML scoring systems and agentic AI solutions that detect and prevent fraud across millions of transactions every day — working at the intersection of streaming data, large language models, and adversarial machine learning to protect customers, merchants, and Walmart's global business.
Job Summary
The Senior Data Scientist – International Anti-Fraud will design, develop, and operationalize real-time machine learning models and agentic AI systems to detect and prevent fraud across all ecommerce touchpoints on Walmart's international digital commerce platforms. You'll own the full ML lifecycle — from feature engineering and model experimentation to sub-millisecond production inference — and build autonomous agentic workflows that augment fraud operations at scale. You'll partner with engineering, product, and risk teams to deliver fraud defenses that are fast, adaptive, and resilient across payment fraud, account takeover, promo/coupon abuse, merchant fraud, and synthetic identity fraud in multiple international markets.
What you'll do...
About the Team
The International Anti-Fraud Data Science team is part of Walmart's International eCommerce organization. We build intelligent, real-time ML and agentic AI systems that safeguard Walmart's global digital commerce platforms — scoring hundreds of millions of transactions with sub-second latency across multiple international markets. Our stack spans streaming inference pipelines, online feature stores, LLM-powered investigation agents, and adaptive fraud models that evolve as fast as the threat landscape does. We operate at the intersection of data science, real-time engineering, and risk — tackling the full spectrum of ecommerce fraud touchpoints including payment fraud, account takeover, synthetic identity fraud, promo/coupon abuse, and merchant abuse. We are a global team that moves fast, operates with data-driven rigor, and deploys solutions that directly impact Walmart's bottom line and customer trust.
**What You'll Do **
- Architect real-time ecommerce fraud detection systems: Design and deploy sub-100ms ML scoring pipelines across all critical ecommerce fraud touchpoints — payment fraud, account takeover, promo/coupon abuse, merchant fraud, and synthetic identity fraud — leveraging streaming architectures (Kafka, Flink) and online feature stores for instantaneous, high-throughput risk decisioning.
- Build and operationalize agentic fraud solutions: Design LLM-powered autonomous agents that investigate suspicious activity, orchestrate multi-step fraud triage workflows, and surface actionable intelligence to fraud operations teams — bringing the power of generative AI and tool-use to fraud detection and response at scale.
- Own the full ecommerce fraud ML lifecycle: Lead initiatives end-to-end — from data exploration and feature engineering through model experimentation, rigorous A/B testing, production deployment, and continuous monitoring, retraining, and adversarial adaptation across international markets.
- Uncover adversarial patterns across fraud touchpoints: Work with large-scale transaction, behavioural, device, and identity data to identify fraud rings, emerging attack vectors, and cross-touchpoint fraud patterns using advanced ML techniques including graph-based models, sequence models, and anomaly detection.
- Drive cross-functional fraud strategy: Partner with engineering, product, risk operations, and business stakeholders across international markets to translate fraud requirements into production-grade real-time ML and agentic systems — communicating model behaviour and fraud trends clearly to both technical and executive audiences
What You'll Bring
- Applied ecommerce fraud ML expertise: 3–7 years of hands-on data science experience with a strong focus on ecommerce fraud — payment fraud, account takeover, promo abuse, merchant fraud, or synthetic identity fraud — ideally in a high-volume, real-time production environment.
- Real-time systems and streaming ML: Proven experience building low-latency ML inference pipelines using streaming platforms (Kafka, Flink, Spark Streaming) and online feature stores, with a strong grasp of the engineering constraints of sub-second fraud decisioning at scale.
- Agentic AI and LLM development: Hands-on experience building or prototyping agentic systems using LLM frameworks (LangChain, LlamaIndex, or similar), multi-agent orchestration, tool-use patterns, or GenAI-powered automation workflows — applied to operational, risk, or investigative use cases.
- Strong ML engineering and MLOps fundamentals: Proficiency in Python, with expertise in ML frameworks (XGBoost, LightGBM, PyTorch/TensorFlow) and production ML practices including model monitoring, drift detection, feature stores, and CI/CD pipelines for continuous model delivery.
- Communication and cross-functional influence: Strong analytical storytelling skills — ability to translate complex model behavior, fraud trends, and agentic system design into clear insights and recommendations that drive alignment across product, engineering, risk, and business teams in a global, matrixed organization.
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 expert's 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.
Mode of Work
Walmart’s culture sets us apart, and we know being together helps us innovate, learn and grow great careers. This role is based in our Bangalore office for daily work, with the flexibility for associates to manage their 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.
Minimum Qualifications...
__Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications. __
Minimum Qualifications:Option 1- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 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 1 years' experience in an analytics related field. Option 3 - 5 years' experience in an analytics or related field.
Preferred Qualifications...
__Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications. __
Primary Location...
Block- 1, Prestige Tech Pacific Park, Sy No. 38/1, Outer Ring Rd Kadubeesanahalli , India