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Senior Fraud Investigations Analyst

90k – 120kMcLean, VAOtherOnsite4+ YOE
Summary

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.

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
Skills
SQLPythonMachine LearningFraud Detection ToolsRisk ScoringAILLMData AnalysisThreat IntelligenceBehavioral Analysis
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