Risk Manager, Payment Fraud Operations

Fraud Risk Decisioning 

• Analyze incoming transactions, customer, and usage signals to identify fraudulent behavior and make accurate, risk-based accept/reject decisions.  

Risk Insights & Emerging Pattern Clustering:  

• Identify emerging fraud patterns and root causes using transaction and usage data, translating insights into improved automated treatment strategies.  

Customer Remediation: 

• 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. 

Continuous Improvement & Operational Excellence: 

• 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.  

Risk Model & Control Feedback: 

• 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. 

Operations OKR Performance Management:  

• Monitor and improve key metrics including accuracy, false positive/negative outcomes, decision time, productivity, and customer impact.  

Operations Strategy & Process Improvement:  

• Develop preventative measures, process enhancements, and scalable solutions to address emerging risks and operational gaps.  

Stakeholder Collaboration & Communication:  

• 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. 

Risk Governance & Communication:  

• Communicate fraud trends, quality insights, process changes, and risk concerns to stakeholders and senior leaders.  

Capability Development:  

• Develop guidelines, documentation, and training and support adoption of new tools, processes, investigation guidelines and controls.  

• Embody our culture and values

Required Qualifications:  

• 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.

Preferred Qualifications: 

• 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.