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 ourcultureandvalues

Required Qualifications:

• Bachelors 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:

• Bachelors 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.