Abuse Research Engineer

Stripe

. Conduct hypothesis-driven proactive threat hunting across Stripe systems and external data .

Posted 9/30/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in threat intelligence and hunting, with a strong ability to analyze complex datasets and automate workflows using Python and SQL. Proficient in translating technical findings into actionable strategies while collaborating effectively across multiple teams.

Highest-signal resume keywords

Threat IntelligencePython ProgrammingSQL ProficiencyData AnalyticsCyber Investigation Methodologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Threat HuntingData AnalysisLog AnalysisDigital ForensicsAutomated TestingFraud DetectionComplex Dataset AnalysisScriptingInvestigative Tool DevelopmentVulnerability Identification

Soft Skills

Strong Communication Skills

Tools & Technologies

DatabricksTrinoPySparkPandasScikit-LearnTIPsOSINTBreach IntelligenceAgentic LLM Tools

Industry Keywords

Cyber SecurityProduct AbuseTrust DomainsFinancial-Fraud Threat ActorsTTPsFT3 TaxonomyMITRE ATT&CK

Tech Stack

Tools & technologies

Cyber SecurityPandasPySparkPythonScikit-LearnSQL

About the role

Key responsibilities & impact

Conduct hypothesis-driven proactive threat hunting across Stripe systems and external data
Analyze adversary behavior and complex fraud vectors using Stripe’s FT3 taxonomy
Integrate, curate, and automate threat intelligence feeds into engineering workflows
Translate research findings into threat advisories and strategic control recommendations
Simulate adversary tactics, techniques, and procedures using agentic automated testing frameworks
Validate deployed controls and generate regression scenarios
Collaborate with Fraud Ops, Strategy, Risk, Onboarding, Security, and Fraud Intelligence teams
Identify and systematically eliminate product vulnerabilities

Requirements

What you’ll need

5+ years of experience conducting threat intelligence, threat hunting, or technical incident response within cyber security, product abuse, or trust domains
5+ years of experience analyzing large, complex datasets using data analytics tools to identify anomalies, map behavioral trends, and solve complex fraud problems
B.S. or M.S. in Computer Science, Cybersecurity, or a related technical field, or equivalent practical experience
Expert proficiency in Python and SQL, with demonstrated experience using code and scripting to automate workflows, build investigative tools, or query big data pipelines
Hands-on experience in log analysis, digital forensics, and cyber investigation methodologies
Strong communication skills with ability to translate complex technical research into actionable recommendations
Preferred: understanding of financial-fraud threat actors and TTPs, FT3 or MITRE ATT&CK, Databricks, Trino, PySpark, Pandas, Scikit-Learn, TIPs, OSINT, breach intelligence, agentic LLM tools, automated testing, and relevant certifications