Data Scientist III

About the role

Sam’s Club is seeking a Data Scientist III to join their fraud detection team. This role involves owning fraud risks in various product segments and collaborating with product and business teams to set goals, create strategy, and drive innovation in fraud detection.

Responsibilities

• Develop and implement machine learning models for fraud detection in areas such as E-Commerce & In-club payment fraud, Return abuse, Account takeover (ATO) etc.
• Design and implement graph-based fraud detection systems, including link analysis, entity resolution, and Graph Neural Network (GNN) models to detect coordinated fraud rings and network-level risk signals.
• Leverage Generative AI techniques (e.g., LLMs and Agentic workflows) to enhance fraud detection, automate investigation workflows, generate risk narratives, and improve model explainability.
• Partner with business and technical stakeholders to translate fraud business problems into data science solutions.
• Work on highly-scalable ML models and algorithms in big data mining, graph modeling & other domains.
• Work with engineering teams to implement model pipeline and deploy the service at scale.
• Swiftly respond to system issues and conduct root cause analysis.

Requirements

• Industry experience in building production machine learning systems at scale.
• 3-5 years of experience with languages used to manipulate data and draw insights from large data sets (e.g. Python, SQL, etc.).
• Experience working with large data sets and distributed computing tools (PySpark/GCP/BigQuery).
• Hands-on experience or strong familiarity with Graph Neural Networks (GNNs), graph embeddings, or large-scale graph processing frameworks.
• Experience exploring or applying Generative AI / LLM-based approaches for decision intelligence, feature generation, workflow automation, or explainability.
• Experience in fraud risk solutions is desirable.
• Experience in working with cross-functional product and engineering teams to understand requirements and incorporate them in the roadmap.

Qualifications

• Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics or related field.
• Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field.
• 4 years' experience in an analytics or related field.

Skills

• Industry experience in building production machine learning systems at scale.
• Experience with large data sets and distributed computing tools (PySpark/GCP/BigQuery).
• Hands-on experience or strong familiarity with Graph Neural Networks (GNNs), graph embeddings, or large-scale graph processing frameworks.
• Experience exploring or applying Generative AI / LLM-based approaches for decision intelligence, feature generation, workflow automation, or explainability.
• Experience in fraud risk solutions is desirable.
• Experience in working with cross-functional product and engineering teams to understand requirements and incorporate them in the roadmap.

Benefits

• Competitive pay with performance-based bonus awards.
• Flexible, hybrid work schedule.
• Health benefits including medical, vision, and dental coverage.
• Financial benefits such as 401(k), stock purchase, and company-paid life insurance.
• Paid time off benefits including PTO, parental leave, family care leave, bereavement, jury duty, and voting.
• Short-term and long-term disability, company discounts, military leave pay, adoption and surrogacy expense reimbursement, and more.
• Education benefits through Live Better U.