Fraud Strategist

Details

Stripe is a financial infrastructure platform for businesses. The Fraud Strategy team builds scaled fraud mitigation systems that prevent fraud and protect the financial ecosystem while minimizing disruption to legitimate users.

As a Fraud Strategist, you will build strategies to mitigate buyer, seller, and account fraud across new and existing Stripe products. You will partner with Product, Engineering, Data Science, Operations, Risk Partnerships, and other Risk Strategy teams to embed fraud controls across products and payment methods globally. You will also help innovate Stripe's approach to scalable fraud risk management.

Responsibilities

• Monitor portfolios to identify, mitigate, and predict risky behavior that could result in losses for Stripe, its users, or the broader financial ecosystem.
• Collaborate with Product, Engineering, Data Science, Risk Partnerships, and Operations to tailor fraud risk management techniques to different products and payment methods worldwide.
• Evaluate products for risk-control gaps and propose improvements that support growth.
• Scale risk processes across a complex fraud landscape by designing, outsourcing, and automating manual or repetitive workflows.
• Educate Stripe users and guide them on preventing potential fraud risks to their businesses.
• Communicate clearly with Stripe employees, users, financial partners, and regulatory partners.

Requirements

• 5+ years of relevant experience, preferably in financial services, payments, or fintech.
• Curiosity and passion for risk management, including investigating anomalies and solving root causes.
• Decisiveness, openness to learning, and comfort making high-impact decisions.
• Data-driven judgment and the ability to use quantitative analysis to make and defend decisions.
• Empathy for early-stage businesses and the ability to balance enforcement with user experience.
• Strong analytical skills, including the ability to frame complex tradeoffs using data and visualization.
• Advanced SQL skills with hands-on business experience.
• Proven ability to collaborate and execute cross-functionally with Engineering, Product, Data Science, and Operations.
• Excellent written and verbal communication skills.
• Holistic thinking and the ability to build scaled processes that bridge systemic gaps.
• A track record of deriving actionable insights from complex problem spaces and influencing product direction.
• Ownership mentality and the ability to lead without formal authority.
• Proficiency with AI tools to accelerate productivity and process automation.

Preferred Qualifications

• Expertise with quantitative tools such as Python or R.
• Experience with payments, risk, or trust and safety.
• Experience working with machine learning teams.
• Experience in fast-paced and rapidly changing startup environments.