Fraud Strategist
The Fraud Strategist develops and scales fraud controls across payment products, using quantitative analysis to identify risky behavior, guide decisions, and balance enforcement with user experience. The role requires cross-functional collaboration and advanced SQL, with payments or risk experience preferred.
About the job
Responsibilities
- Monitor portfolios to identify, mitigate, and predict risky behavior that could result in losses for Stripe, its users, and the financial ecosystem.
- Collaborate with Product, Engineering, Data Science, Risk Partnerships, and Operations to tailor fraud risk management techniques across products and payment methods globally.
- Evaluate products for fraud-control gaps and propose controls that enhance products while enabling 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 internal teams, users, and financial 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.
- Decisive, open to learning, and comfortable making high-impact decisions.
- Data-driven judgment and strong quantitative analysis skills.
- Ability to balance fraud enforcement with user experience.
- Strong analytical, data visualization, and complex tradeoff-framing skills.
- Advanced SQL skills with hands-on business experience.
- Proven cross-functional collaboration with Engineering, Product, Data Science, and Operations.
- Excellent written and verbal communication skills.
- Ability to build scaled processes that address systemic gaps.
- Track record of deriving actionable insights from complex problems and influencing product direction.
- Ownership mentality and ability to lead without formal authority.
- Proficiency with AI tools for productivity and process automation.
Nice-to-haves
- 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, rapidly changing startup environments.
Skills
SQL, Python, R, Machine Learning, Data Visualization, Fraud Risk Management, Payments, Risk Management, Trust And Safety, Process Automation, Artificial Intelligence, Quantitative Analysis
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