Fraud Risk Strategist: Rules, Scoring & Insights

Early Warning Services LLC; Scottsdale (AZ); Hybrid; USD 84,000 - 105,000; Full time

Benefits offered by this job

Healthcare Coverage

401(k) Match

Paid Time Off

Job summary

Early Warning Services LLC is seeking a Fraud Risk Analyst in a hybrid role based in the Scottsdale area. You will analyze and deploy rules and scoring logic from fraud models to optimize risk, cost and user experience across payment networks.

The role partners with Product, Engineering and Analytics to shape fraud strategies, monitor threats, and drive data-driven decisions. A strong analytics background and 5+ years in fraud risk are essential.

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 ability to translate concepts into analysis and change.
• Strong written, verbal, and presentation skills for technical and non-technical audiences.
• Experience with digital banking, payments and/or payment networks.
• Experience with financial institutions in fraud risk management.
• Background check

Responsibilities

• Assess, recommend and modify the application of scores and rules to balance risk, expense and experience for clients and partners.
• Implement fraud detection and prevention strategies for the network.
• Create data-driven insights for monitoring effectiveness and opportunities in rules and logic.
• Prepare clear communications for internal and external stakeholders about risks and trends.
• Analyze fraud events to identify root causes and mitigation opportunities.
• Monitor fraud trends and proactively enhance rules, strategies and controls.
• Protect the integrity and confidentiality of systems and data.

Skills

SQL

SAS

Python

Data analytics

Education

Bachelor's degree or equivalent education/experience

Job description

Early Warning Services LLC is seeking a Fraud Risk Analyst in a hybrid role based in the Scottsdale area. You will analyze and deploy rules and scoring logic from fraud models to optimize risk, cost and user experience across payment networks.

The role partners with Product, Engineering and Analytics to shape fraud strategies, monitor threats, and drive data-driven decisions. A strong analytics background and 5+ years in fraud risk are essential.