Fraud Abuse Specialist, Digital Fraud & Abuse

GEICO GEICO · Insurance · Bethesda, MD +3

This role focuses on developing and maintaining advanced fraud models using machine learning and data science techniques. It involves analyzing complex data sets, integrating third-party data, monitoring model performance, and conducting risk assessments. A key aspect is leveraging agentic AI systems to automate workflows and enhance fraud detection capabilities within the digital fraud domain at GEICO.

What you'd actually do

  1. Develop and maintain advanced fraud models to identify identity fraud, account takeover, and synthetic identity risks.
  2. Perform risk analyses and manage complex data sets using tools such as SQL, Python, and R.
  3. Monitor fraud analytics encompassing Identity and Entity Resolution/Detection, Social Network Analysis, and Unsupervised Monitoring techniques.
  4. Integrate data from third-party technology providers and tools to continuously enhance fraud detection capabilities.
  5. Utilize agentic AI systems to automate workflows, enhance pattern detection, and expedite investigation and detection initiatives.

Skills

Required

  • SQL
  • Python
  • R
  • machine learning
  • data science
  • API understanding
  • data workflows
  • customer environments
  • relational and non-relational database systems
  • data visualization
  • dashboard creation
  • Tableau
  • Bachelor’s degree in Math, Statistics, Computer Science, or related Science field, or experience in data science, machine learning or data mining
  • 5+ years of relevant analytic experience in within digital fraud, abuse prevention, identity risk, and related fields
  • Experience working with data and technology teams to build machine learning and heuristic fraud signals and rules
  • Experience partnering closely with product and engineering teams on platform evolution

Nice to have

  • Insurance
  • fintech
  • large‑scale consumer digital platform experience
  • adaptive authentication
  • device intelligence
  • risk engines
  • programmatic fraud prevention capabilities

What the JD emphasized

  • develop fraud analytics models
  • machine learning
  • agentic AI systems

Other signals

  • develop fraud analytics models
  • apply advanced data analysis skills—including SQL, Python, machine learning
  • leverage data and technical expertise to discover innovative approaches to scaling signal analysis and identifying fraudulent actors
  • Utilize agentic AI systems to automate workflows, enhance pattern detection, and expedite investigation and detection initiatives