Payments & Fraud Analyst: Data-Driven Risk & Revenue

Candidate; San Francisco, Northern (CA, KY); Hybrid; USD 144,000 - 162,000; Full time

Benefits offered by this job

Relocation assistance

Equity

Benefits package

Job summary

Discord in San Francisco is seeking a Payments & Fraud Analyst to own end-to-end fraud detection, payments operations, and risk assessment within a high-scale environment. You’ll collaborate across Engineering, Legal, Product, and Revenue to shape policies and drive revenue protection.

You’ll analyze data with SQL, build dashboards in Mode and Datadog, mentor teammates, and lead cross-functional programs to mitigate fraud while enabling growth and reliable transactions.

Qualifications

• 4–5+ years of experience in payments, fraud, or risk operations
• Deep knowledge of payments flows and card network rules (Visa, Mastercard, Amex)
• Proficiency in SQL for querying and analyzing large datasets
• Experience building reporting and monitoring workflows with BI and alerting tools
• Proven ability to own end-to-end functions and lead mid-size programs
• Strong written and verbal communication skills and cross-functional collaboration

Responsibilities

• Own high-scale fraud detection and mitigation, payments operations, and risk assessment within your area end-to-end
• Lead high complexity fraud investigations and propose rule improvements
• Write SQL queries and build dashboards/alerts (Mode, Datadog) to track performance
• Program manage cross-functional initiatives with Engineering, Legal, Product, Revenue
• Contribute to risk assessments for new product launches and mitigation planning
• Mentor junior team members and share knowledge across the team

Tools

Mode

Datadog

Job description

Discord in San Francisco is seeking a Payments & Fraud Analyst to own end-to-end fraud detection, payments operations, and risk assessment within a high-scale environment. You’ll collaborate across Engineering, Legal, Product, and Revenue to shape policies and drive revenue protection.

You’ll analyze data with SQL, build dashboards in Mode and Datadog, mentor teammates, and lead cross-functional programs to mitigate fraud while enabling growth and reliable transactions.