Bachelor's degree in a quantitative field (Economics, Computer Science, Statistics, Mathematics preferred)
4+ years in fraud investigations, threat intelligence, cybersecurity, or risk management, focusing on account takeover (ATO)
2+ years using SQL, Python, or similar tools for data analysis
2+ years with fraud detection tools, machine learning models, or risk-scoring methodologies
2+ years interpreting fraud indicators and transaction monitoring data
Experience analyzing fraud trends beyond individual cases, including pattern detection
Familiarity with AI/LLM tools for data analysis and validation
Responsibilities
Lead complex ATO investigations, focusing on multi-account and organized fraud
Analyze large datasets to identify trends and attack patterns using SQL or Python
Utilize fraud detection tools and machine learning outputs to enhance investigations
Independently manage investigations from detection to resolution with thorough documentation
Identify and address gaps in detection logic, contributing to system improvements
Collaborate with engineering and product teams to enhance fraud detection capabilities
Serve as an escalation point for high-severity fraud cases
Benefits
Comprehensive medical, dental, and vision insurance
Health savings and flexible spending accounts
401(k) plan with company match
Unlimited paid time off and 8 company-wide holidays
Short and long-term disability insurance
Employee assistance program and pet insurance
Learning and development benefits
Full Job Description
Role Overview
ID.me is looking for a Senior Fraud Investigations Analyst to join our organization as an execution-focused individual contributor. This role is responsible for leading investigations into account takeover (ATO) activity, identifying fraud patterns at scale, and strengthening detection strategies.
We are seeking a highly skilled analyst who can independently analyze large datasets, uncover coordinated fraud campaigns, and drive improvements in detection systems. This role requires moving beyond case-by-case investigation into trend analysis, signal development, and data-driven decision making.
This role is based out of our McLean, VA office and requires full-time in-office attendance. 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
Bachelor's degree from an accredited institution; strong preference for quantitative fields such as Economics, Computer Science, Statistics, Mathematics, or similar
4+ years of experience in fraud investigations, threat intelligence, cybersecurity, or risk management, with a focus on account takeover (ATO) attacks (typically 4-8 years total experience; candidates should have )
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
The annual base salary listed does not include a company bonus, incentive for sales roles, equity and benefits which will be determined based on experience, skills, education, relevant training, geographic location and role.
IDMe offers comprehensive medical, dental, vision, health savings account, flexible spending accounts (medical, limited purpose, dependent care, commuter benefit accounts), basic and voluntary life and AD&D insurance, 401(k) with company match, parental leave, ability to participate in unlimited paid time off subject to the terms and conditions of the PTO policy, including 8 company wide holidays, short and long-term disability insurance, accident and critical illness insurance, referral bonus policy, employee assistance program, pet insurance, travel assistant program, wellbeing and childcare discounts, benefit advocates, and a learning and development benefit.
Final offers may vary from the amount listed based on qualifications, professional experiences, skills, education, relevant training, geographic location, and other job related factors.
