Walmart
Position Summary
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 including semi-supervised learning, agentic AI, continual learning, and 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
PhD or Master’s in Computer Science, Statistics, Mathematics, or a related field, with a strong foundation in machine learning, data science, and statistical modeling preferred, or relevant work experience. Expertise in Fraud Detection & Risk Modeling (Preferred). Proficiency in building production-ready ML systems, including real-time and batch inference, feature engineering, and model optimization. Familiarity with Python, SQL, Spark, and ML frameworks (e.g., TensorFlow, PyTorch, XGBoost). Demonstrated ability to explore and apply advanced ML techniques (e.g., semi-supervised learning, continual learning, anomaly detection) to complex problems, ideally with published work or patents. Deep understanding of model governance practices including fairness, explainability, drift detection, and documentation. Experience implementing responsible AI frameworks in production environments. Strong track record of working with engineering, product, and platform teams to integrate ML solutions into business workflows. Ability to lead technical decision-making in pod-based teams. Experience mentoring senior data scientists and leading initiatives to standardize modeling practices across experimentation, deployment, and monitoring. Ability to translate complex technical concepts into actionable insights for non-technical stakeholders and represent the team in enterprise-wide forums. At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. 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 Walmart\'s notices at 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. Primary Location
Primary Location:
860 W California Avenue, Sunnyvale, CA 94086-0000, United States of America
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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 including semi-supervised learning, agentic AI, continual learning, and 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
PhD or Master’s in Computer Science, Statistics, Mathematics, or a related field, with a strong foundation in machine learning, data science, and statistical modeling preferred, or relevant work experience. Expertise in Fraud Detection & Risk Modeling (Preferred). Proficiency in building production-ready ML systems, including real-time and batch inference, feature engineering, and model optimization. Familiarity with Python, SQL, Spark, and ML frameworks (e.g., TensorFlow, PyTorch, XGBoost). Demonstrated ability to explore and apply advanced ML techniques (e.g., semi-supervised learning, continual learning, anomaly detection) to complex problems, ideally with published work or patents. Deep understanding of model governance practices including fairness, explainability, drift detection, and documentation. Experience implementing responsible AI frameworks in production environments. Strong track record of working with engineering, product, and platform teams to integrate ML solutions into business workflows. Ability to lead technical decision-making in pod-based teams. Experience mentoring senior data scientists and leading initiatives to standardize modeling practices across experimentation, deployment, and monitoring. Ability to translate complex technical concepts into actionable insights for non-technical stakeholders and represent the team in enterprise-wide forums. At Walmart, we offer competitive pay as well as performance-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short-term and long-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. 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 Walmart\'s notices at 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. Primary Location
Primary Location:
860 W California Avenue, Sunnyvale, CA 94086-0000, United States of America
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