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Microsoft

Risk Manager Payment Fraud Operations United States Washington Redmond

Microsoft

Full-timeOn-sitePosted 7 October 2026
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Job description

Fraud Risk Decisioning Analyze incoming transactions, customer, and usage signals to identify fraudulent behavior and make accurate, risk-based accept/reject decisions. Support incident management, root-cause analysis, and remediation for payment-fraud issues. Provide high-quality decisioning, fraud labels and investigation insights to support risk model refinement, policy improvements, and preventative controls. Develop preventative measures, process enhancements, and scalable solutions to address emerging risks and operational gaps. Develop guidelines, documentation, and training and support adoption of new tools, processes, investigation guidelines and controls. Bachelor's Degree in Risk Management, Engineering, Government Intelligence, Security, or Information Technology, or related field AND 2+ years experience in risk management, privacy, security, compliance, government intelligence, operations, auditing, and/or finance OR equivalent experience. Bachelor's degree in Business, Finance, Risk Management, Data Analytics, Computer Science, or a related field, or equivalent practical experience. 5+ years of experience in fraud risk management, payments, financial crime, trust & safety, risk operations, or a related field. Experience analyzing transaction, customer, and usage data to identify fraud patterns, emerging risks, and root causes. Experience with risk decisioning, fraud detection strategies, risk models, rules, or control frameworks, including translating operational insights into risk improvements. Strong analytical and problem-solving skills, with experience using data to identify trends, diagnose quality gaps, and drive preventative actions. Experience driving continuous improvement and operational efficiency, including process simplification, automation, tooling enhancements, and reduction of manual effort or rework. Experience working cross-functionally with Engineering, Data Science, Operations, Customer Support, and Product/Business teams to implement scalable risk solutions. Experience establishing and managing risk and operational KPIs, such as decision accuracy, false positive/negative rates, productivity, turnaround time, customer impact, and fraud loss. Strong communication and stakeholder management skills, with the ability to translate complex risk insights into clear recommendations for both technical and senior business audiences. Experience developing SOPs, risk guidelines, training programs, and governance mechanisms to drive consistent decision-making and operational quality. Familiarity with SQL, Kusto, Power BI, or other data analytics and visualization tools is preferred. Basic experience building or configuring AI agents, including developing clear Markdown-based instructions, setting up simple workflows, connecting relevant tools or information sources, and testing and refining outputs. Ability to operate effectively in a fast-paced, ambiguous, and globally distributed environment, balancing customer experience, fraud risk, operational efficiency, and business impact.

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