Abuse Research Engineer

Job Description

REQUIREMENTS

• 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 (e.g., application logs, API route telemetry, network security events), digital forensics, and cyber investigation methodologies.  
• Strong communication skills with a proven ability to translate complex technical research into clear, actionable recommendations and advisories for cross-functional partners.

Preferred

• Deep technical understanding of threat actor motivations, infrastructure, and TTPs specific to financial fraud (e.g., ATO, Card Testing, Credential Stuffing). 
• Familiarity with standardized taxonomies such as FT3 or MITRE ATT&CK.  
• Proficiency with engineering, data processing, and analysis platforms such as Databricks, Trino, PySpark, Pandas, or Scikit-Learn.  
• Proven background utilizing Threat Intelligence Platforms (TIPs), tactical threat feeds, OSINT, and breach intelligence. 
• Demonstrated capability building or leveraging agentic LLM tools, automated testing systems, or control validation frameworks to model adversary behavior at scale. 

RESPONSIBILITES

• Proactive Threat Hunting & Kill Chain Analysis: Formulate hypotheses and conduct iterative threat hunting operations across Stripe systems and external data.
• FT3 Taxonomy: Apply and enrich the FT3 framework across empirical datasets and incidents, standardizing threat intelligence across kill chain phases and targeted API endpoints.  
• Threat Intelligence & Signal Expansion: Partner with teams like Fraud Intelligence to integrate, curate, and automate threat feeds into engineering workflows.  
• Cross-Functional Advisories & Strategic Controls: Translate raw research and retrospective findings into actionable threat advisories and control recommendations (policy, technical systems, support workflows, and detection mechanisms) for stakeholders across Fraud, Risk, Onboarding, and Security.  
• Agentic Testing & Adversary Simulation: Utilize agentic automated testing frameworks to simulate adversary TTPs, validate whether deployed controls interrupt empirical kill chains, and generate regression scenarios to exercise controls.

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