Abuse Investigator
Investigates high-risk accounts and leads incident response for fraud and product-abuse events, using behavioral analysis and threat intelligence to identify root causes and improve detection. Requires 3+ years of incident response and fraud-data analysis experience, plus strong Python and SQL skills.
About the job
Responsibilities
- Investigate, mitigate, and remediate urgent fraud incidents, including account takeovers and card testing, using detection and signal-enrichment methods.
- Analyze high-risk accounts to identify fraudulent merchants, card testing, account takeovers, and other fraud vectors; classify threats using the Fraud Taxonomy 3.0 framework.
- Lead incident root-cause analyses to identify system and strategy gaps and drive data-informed improvements for emerging fraud risks.
- Improve incident-response tooling and processes for clarity, accuracy, and efficiency.
- Collaborate with security, fraud, and data science teams to build agentic solutions for responding to abuse incidents at scale.
- Work with legal and policy teams to assess and mitigate risks.
- Lead projects, mentor teammates, and develop quality standards.
Requirements
- 3+ years of experience conducting incident response in security, product abuse, or trust domains.
- 3+ years of experience analyzing large datasets to solve problems and/or building behavioral models for fraud detection.
- Bachelor's or master's degree in Computer Science or a related field, or equivalent experience.
- Expert knowledge of Python and SQL; familiarity with other programming languages.
- Experience with log analysis, network security, digital forensics, and incident-response investigations.
- Strong communication, problem-solving, and risk-reduction skills.
Preferred Qualifications
- Adversarial mindset and understanding of threat-actor goals, behaviors, and tactics, techniques, and procedures.
- Experience with engineering, data-processing, and analysis tools such as Databricks and Trino.
- Familiarity with big-data and data-science frameworks such as PySpark, Pandas, and scikit-learn.
- Experience with tactical threat intelligence and threat hunting for sophisticated enterprise threat actors.
- Ability to use data and a user-centric approach to address complex product-integrity challenges.
Skills
Python, SQL, Log Analysis, Network Security, Digital Forensics, Incident Response, Fraud Detection, Databricks, Trino, Pyspark, pandas, scikit-learn, Threat Intelligence, Threat Hunting, Data Analysis
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