Sr. Fraud Risk Strategies Analyst - Paze

At Early Warning, we’ve powered and protected the U.S. financial system for over thirty years with cutting-edge solutions like Zelle®, Paze℠, and so much more. As a trusted name in payments, we partner with thousands of institutions to increase access to financial services and protect transactions for hundreds of millions of consumers and small businesses.

Positions located in Scottsdale, San Francisco, Chicago, or New York follow a hybrid work model to allow for a more collaborative working environment.

Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire. This position is ineligible for employment Visa sponsorship.

Overall Purpose

This role is accountable to analyze, create and deploy the rules, scores, and decisioning logic from both internally and externally developed fraud risk models and applications with the associated outcomes as it applies to decisions rendered to optimize the balance of risk, expense and experience while using the payment network in a variety of operating environments.

This work must be done directly or in partnership with financial institutions and includes collaboration with internal stakeholders including Product, Engineering, and Analytics to inform fraud risk decisioning and strategy execution. This role also partners closely with Fraud Risk Program Management to align fraud strategies with broader program objectives and roadmap priorities.

Essential Functions 

• Assess, recommend and modify the application of scores and rules to deliver the optimal balance of risk, expense and experience for clients, consumers and partners in the network.

• Implement fraud detection and prevention strategies for the network.

• Create and apply data-driven insights for constant monitoring of effectiveness, efficiency and opportunities in the application of features, scores, rules and logic to continuously improve fraud risk strategy performance.

• Develop and deliver clear, concise communications and presentations to internal stakeholders (including Product, Engineering, Analytics, and Risk teams) external stakeholders (including banking partners, merchants, and third-party vendors) regarding emerging risks, observed trends and related opportunities.

• Perform the analysis of fraud events for the purpose of identifying and consistently categorizing the root cause of fraud events observed or attempted in the network and identifying control gaps and opportunities for mitigation.

• Monitor fraud trends, emerging threats, and attack patterns, and proactively recommend enhancements to rules, strategies, and controls.

• Support the company’s commitment to protect the integrity and confidentiality of systems and data.

Minimum Qualifications

• Bachelor’s degree or equivalent education/experience required.

• Minimum 5 years of fraud risk management experience.

• SQL/SAS/Python competencies or comparable data analytics skills.

• Proven track record of converting concepts to analysis to cases for change.

• Strong written, verbal, and presentation skills with the ability to communicate effectively to both technical and non-technical audiences.

• Experience with digital banking, payments and/or payment networks.

• Experience with financial institutions in the area of fraud risk management.

• Background and drug screen

Preferred Qualifications

• Certified Fraud Examiner (CFE) certification or similar credential is a plus

• Ability to operate with a high degree of autonomy and influence strategy decisions without direct authority

• Experience supporting enterprise fraud programs or large-scale fraud platforms

The above job description is not intended to be an all-inclusive list of duties and standards of the position.  Incumbents will follow instructions and perform other related duties as assigned by their supervisor.

Physical Requirements

Working conditions consist of a normal office environment.  Work is primarily sedentary and requires extensive use of a computer and involves sitting for periods of approximate