Safeguards Enforcement Analyst, Fraud & Scams

About the role

As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm.

Your initial focus will be standing up fraud & scams enforcement as a program: today this work is handled reactively and in fragments — payment fraud, promotional abuse, and scam-pattern enforcement don't yet have a single owner. You'll be that owner: defining the policy area, building the detection-to-enforcement pipeline, and setting the operating model that a contractor bench can execute against.

The surface area is broad: payment fraud (stolen cards, chargebacks, disputes), promotional and credits abuse, and the use of accounts to run scams against third parties.

Key Responsibilities

• Define the fraud & scams policy taxonomy and how cases are classified, prioritized, and escalated
• Investigate and dismantle organized abuse rings, converting findings into durable controls
• Stand up proactive fraud detection and customer-facing communication flows for fraudulent organization cases
• Build the dispute and chargeback strategy in partnership with payments and card-network partners
• Quantify fraud losses and control efficacy to drive investment decisions
• Author the contractor playbook for fraud review and own QA of scaled output
• Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows

Minimum Qualifications

• Deep payment-fraud experience at a fintech, marketplace, or platform — chargebacks, disputes, card-testing, promotional abuse
• Experience building or significantly scaling a fraud program from an early state, not just operating a mature one
• A working command of payment-network and dispute mechanics, sufficient to make strategy calls on them
• Comfort being the sole owner of an area: prioritizing ruthlessly, shipping iteratively, and asking for help precisely
• Comfort using data (SQL or similar tools) to quantify fraud losses and control efficacy
• Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders
• Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams

Preferred Qualifications

• Experience working directly with payment service providers and card networks on fraud strategy
• Experience with scam typologies beyond payments — social engineering, impersonation, platform-mediated scams
• Experience managing vendor relationships in the fraud/risk detection space
• A deep interest in AI safety and responsible technology development
• Experience writing effective prompts for generative AI systems in a content review or enforcement context