# Fraud Strategist

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** Unspecified
**Role:** Business Operations
**Experience:** 5+ years
**Skills:** SQL, Python, R, Machine Learning, Data Visualization, Fraud Risk Management, Payments, Risk Management, Trust And Safety, Process Automation, Artificial Intelligence, Quantitative Analysis
**Posted:** 2026-08-21

> 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.

## Job Description

## 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.

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