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Microsoft

Risk Manager, Payment Fraud Operations

Reposted 3 Days Ago
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In-Office
Redmond, WA, USA
78K-170K Annually
Senior level
In-Office
Redmond, WA, USA
78K-170K Annually
Senior level
Leads payment fraud risk operations by analyzing transactions and customer signals, making risk-based decisions, identifying emerging fraud patterns, and improving controls, models, workflows, and remediation. Partners with Engineering, Data Science, Customer Support, and Operations on incident resolution, root-cause analysis, KPI management, process improvement, governance, training, and scalable fraud-prevention strategies.
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Overview

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.


Responsibilities

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

Qualifications

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. 


Risk Management IC3 - The typical base pay range for this role across the U.S. is USD $77,800 - $153,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $102,200 - $169,900 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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