Description
Job Description
Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world's largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet.
Abuse Operations is the front-line incident response and remediation function handling active product abuse and fraud impacting Stripe and its merchants. This multi-disciplinary group neutralizes active attacks, gathers requirements for operational tooling, and leads incidents.
In this role, you will play a critical part in safeguarding our financial ecosystem by investigating high-risk accounts, identifying complex fraud patterns, performing post-incident analyses, and driving cross-functional improvements to scale fraud detection.
Responsibilities
- Lead fraud and abuse incident response end-to-end as Incident Response Manager (IRM), coordinating workstreams, investigating high risk activity and accounts, and making actionable mitigation recommendations under pressure.
- Investigate, mitigate, and remediate urgent fraud incidents (e.g., ATO, card testing), utilizing FT3-mapped (Fraud Taxonomy 3.0) detection and signals enrichment to reduce uncertainty and accelerate response.
- Analyze high-risk accounts to identify fraudulent merchants, card testing, account takeovers, and other fraud vectors, classifying them using FT3 to standardize threat intelligence.
- Develop, document, and execute incident response strategies, runbooks, and capabilities to continuously improve fraud and abuse detection and prevention.
- Partner cross-functionally with security, data science, legal, and policy teams to build agentic response solutions, refine KPIs, and deliver clear incident reporting.
- Mentor teammates, lead key incident response engineering projects, and elevate quality standards across the team.
Requirements
- 10+ years of experience leading security or fraud incident response;
- B.S./M.S. in Computer Science or equivalent experience.
- Expert knowledge of Python and SQL, and familiarity with other programming languages
- Existing experience with log analysis (e.g. first or third party applications, system / data access, event logs), network security, digital forensics, and incident response investigations
- Proven ability to build automated response workflows, leverage threat intelligence, and make risk mitigation recommendations.
- Strong written and verbal communication skills with a track record of driving cross-functional alignment with minimal oversight.
Preferred Qualifications
- Broad expertise across fraud and abuse mitigation, risk management, product trust, and threat intelligence in a complex platform environment.
- An adversarial mindset, understanding the goals, behaviors, and TTPs of threat actors.
- Experience with engineering, data processing and analysis tools (e.g. Databricks, Trino, etc.)
- Familiarity with common open-source frameworks for big data processing and/or data science (PySpark, Pandas, Sci-kit Learn, etc.)
- Experience with tactical threat intelligence and/or hunting for sophisticated threat actors in an enterprise environment
- Ability to proactively challenge the status quo by leveraging data and taking a user-centric approach to address complex product integrity challenges.