# Fraud Strategist

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** Remote
**Role:** Other
**Experience:** 5+ years
**Skills:** SQL, Python, R, AI Tools, Machine Learning
**Posted:** 2026-07-08

> Build and scale fraud mitigation strategies for buyer, seller, and account fraud across Stripe products. Partner with Product, Engineering, and Data Science teams to embed risk controls, monitor portfolios, and drive data-informed decisions that balance safety with business growth.

## Job Description

## Responsibilities
- Monitor portfolio to identify, mitigate and predict risky behavior that could result in losses for Stripe, our users, and the financial ecosystem.
- Collaborate with internal partners like Product, Engineering, Data Science, Risk Partnerships, and Operations, to tailor fraud risk management techniques to various products and payment methods across the globe.
- Continually evaluate products for gaps and propose risk controls to enhance the product while enabling growth.
- Scale risk processes to cover a large and complex landscape of fraud risks. Effectively design, outsource and automate manual/repetitive workflows.
- Work with Stripe users to educate them and guide them on how to prevent potential fraud risks to their business.
- Effectively and clearly communicate with other Stripes, Stripe's users, and Stripe's financial and regulatory partners.

## Minimum Requirements
- 5+ years of relevant experience, preferably in Financial Services, Payments or FinTech.
- Curiosity and passion for risk management - you dig into anomalies and solve root causes.
- Decisiveness and openness to learning, with comfort making high-impact calls daily.
- Data-driven judgment - skilled at using quantitative analysis to drive 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 through data and visualization.
- Advanced SQL skills with hands-on experience in business environments.
- Proven ability to collaborate and execute cross-functionally with Engineering, Product, Data Science, and Operations.
- Excellent written and verbal communication skills, with the ability to convey complex ideas clearly across teams.
- Holistic thinking and the ability to build scaled processes that bridge systemic gaps.
- Track record of deriving actionable insights from complex problem spaces and influencing product direction.
- Ownership mentality and the ability to lead without formal authority.
- Proficient with AI tools to accelerate productivity and process automation.

## Preferred Qualifications
- Expertise with quantitative tools such as Python, R, etc.
- Experience with payments, risk, or trust & safety.
- Experience working with machine learning teams.
- Experience working in fast-paced and rapidly changing start-up environments.

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