Fraud Investigations Analyst

Role Overview

ID.me is looking for an Fraud Investigations Analyst to join our organization as an execution-focused individual contributor. This role centers on investigating account takeover (ATO) activity, analyzing fraud signals, and supporting detection efforts that protect millions of users.

We are seeking someone who goes beyond basic case handling and can analyze trends, identify patterns across multiple accounts, and leverage data to inform investigations. As an Analyst, you will work across fraud detection tools, datasets, and risk systems to uncover coordinated fraud activity and contribute to improving detection capabilities.

This role is based out of our McLean, VA office and requires full-time in-office attendance.

Responsibilities

• Investigate account takeover (ATO) activity using fraud indicators, behavioral signals, and transaction data
• Analyze patterns across multiple accounts to identify coordinated or emerging fraud trends (not just single-account reviews)
• Use SQL, Python, or similar tools to query datasets and support investigations
• Leverage fraud detection tools and risk-scoring systems to identify suspicious activity
• Execute investigations and document findings, escalating higher-risk or complex cases as needed
• Support tuning and optimization of fraud detection rules, alerts, and signal usage
• Partner with cross-functional teams to improve fraud detection coverage and data quality
• Monitor trends in ATO activity and contribute to ongoing detection strategy improvements
• Leverage AI/LLM tools to accelerate investigations, including querying data, identifying patterns, and summarizing fraud activity across accounts

Basic Qualifications

• Bachelor’s degree from an accredited institution; preferred fields include quantitative disciplines such as Economics, Computer Science, Statistics, Mathematics, or similar
• 2+ years of experience in fraud investigations, threat intelligence, cybersecurity, or risk management, with exposure to account takeover (ATO)
• 1+ years of experience using SQL, Python, or similar tools to analyze fraud data or investigate trends
• 1+ years of hands-on experience using fraud detection tools, machine learning models, or risk-scoring methodologies
• 1+ years of experience interpreting fraud indicators, behavioral signals, or transaction monitoring data
• Familiarity with using AI/LLM tools (e.g., ChatGPT, Claude) to support data analysis or investigative workflows

Preferred Qualifications

• Experience working at a fintech company, technology company, or reputable financial institution
• Experience analyzing organized fraud rings or large-scale fraud patterns
• Familiarity with machine learning–driven fraud detection systems or AI-assisted analysis