Incident Response Manager - Abuse Operations

Job Overview

As an Incident Response Manager - Abuse Operations at Stripe, you will play a critical part in safeguarding the company's 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, 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.