Risk Manager, Payment Fraud Operations

Microsoft•Redmond, WA

9h•Onsite

About The Position

The Payment Fraud Operations (PFO) team plays a critical role in protecting Microsoft customers and the broader payment ecosystem from payment fraud. The team combines fraud risk decisioning, operational controls, data-driven insights, and customer remediation to manage emerging payment risks while maintaining a secure and trusted customer experience. We are looking for a Risk Manager, Payment Fraud Operations, based in Redmond, to lead fraud risk management and operational strategy across complex payment and customer scenarios. This role is responsible for identifying and analyzing fraudulent transaction and usage patterns, making risk-based accept/reject decisions, improving fraud prevention controls, and providing robust feedback loops to payment risk models, policies, and detection strategies. The role requires strong risk management expertise, sound judgment, analytical and problem-solving skills, and the ability to influence and collaborate effectively across Operations, Engineering, Data Science, Customer Support, and other business teams. Microsoft's mission is to empower every person and every organization on the planet to achieve more. We foster a culture of growth, innovation, collaboration, respect, integrity, and accountability where everyone can thrive.

Requirements

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.

Nice To Haves

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.

Responsibilities

Analyze incoming transactions, customer, and usage signals to identify fraudulent behavior and make accurate, risk-based accept/reject decisions.
Identify emerging fraud patterns and root causes using transaction and usage data, translating insights into improved automated treatment strategies.
Partner with Customer Support to resolve complex escalations and improve customer remediation strategies. Support incident management, root-cause analysis, and remediation for payment-fraud issues.
Identify and lead opportunities to streamline operations, reduce manual effort and rework, improve workflows and tooling, and increase efficiency without compromising fraud risk controls or decision quality.
Provide high-quality decisioning, fraud labels and investigation insights to support risk model refinement, policy improvements, and preventative controls. Deep dive into quality gaps, identify root causes, and implement improvement strategies and preventative controls to reduce recurrence and strengthen risk outcomes.
Monitor and improve key metrics including accuracy, false positive/negative outcomes, decision time, productivity, and customer impact.
Develop preventative measures, process enhancements, and scalable solutions to address emerging risks and operational gaps.
Partner with Engineering, Data Science, Customer Support, and Operations to drive root-cause analysis and implement risk solutions. Act as the primary Redmond payment-fraud point of contact for Engineering and Customer Support teams.
Communicate fraud trends, quality insights, process changes, and risk concerns to stakeholders and senior leaders.
Develop guidelines, documentation, and training and support adoption of new tools, processes, investigation guidelines and controls.
Embody our culture and values