Leads complex account takeover investigations, analyzes large datasets with SQL/Python to uncover fraud patterns, and improves detection systems. Requires 4+ years in fraud/cybersecurity and bachelor's in quantitative field.
90k – 120k/yr
On-site4+ YOEOther
About the role
Responsibilities
Lead complex account takeover (ATO) investigations, including multi-account and organized fraud activity
Analyze large datasets using SQL, Python, or similar tools to identify trends, anomalies, and attack patterns
Use fraud detection tools, machine learning outputs, and risk-scoring systems to drive high-quality investigations
Independently own investigations from detection through resolution, including clear documentation and recommendations
Identify gaps in detection logic and contribute to improvements in rules, models, and workflows
Partner with engineering, data, and product teams to enhance fraud detection capabilities and signal quality
Act as an escalation point for high-severity or ambiguous fraud cases
Develop and refine investigation playbooks and analytical approaches for ATO detection
Support reporting and analysis of fraud trends, detection performance, and operational metrics
Leverage AI/LLM tools to analyze large datasets, identify fraud patterns, and improve investigation speed and accuracy while validating outputs against source data
Basic Qualifications
4+ years of experience in fraud investigations, threat intelligence, cybersecurity, or risk management, with a focus on account takeover (ATO) attacks
2+ years of experience using SQL, Python, or similar tools to analyze data and drive investigations
2+ years of hands-on experience using fraud detection tools, machine learning models, or risk-scoring methodologies
2+ years of experience interpreting fraud indicators, behavioral signals, or transaction monitoring data
Demonstrated experience analyzing fraud trends beyond individual case investigations (e.g., pattern detection, ring analysis)
Experience using AI/LLM tools to enhance data analysis and investigations, with demonstrated ability to validate and apply outputs effectively
Preferred Qualifications
Experience at a fintech company, technology company, or reputable financial institution
Strong experience analyzing organized fraud rings or large-scale ATO campaigns
Experience influencing fraud detection logic, models, or rule systems
Familiarity with AI/ML techniques applied to fraud detection and risk analysis
Ability to translate analytical findings into actionable improvements for product, engineering, or risk systems
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