Fraud Data Analyst
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Some ghost-posting signals
- open for 121 days (90+ without a fill is a strong ghost signal)
- 59 open roles at this company in 30 days (mass-hiring blitz)
- no salary disclosed (correlates with ghost postings)
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About the role
Key Responsibilities
Data Instrumentation: Collaborate with Product and Engineering to define requirements for capturing fraud signals.
Analysis & Detection: Identify anomalies, suspicious patterns, and credit fraud indicators like manipulated documents or synthetic identities.
Investigation: Conduct deep dives into high-risk users and transactions to uncover new fraud typologies.
Logic Implementation: Translate insights into fraud detection rules, monitoring systems, and risk models.
Requirements
Years of Experience: Minimum of 5 years in fraud-related roles within Financial Services (Banking, Fintech, or Digital Lending).
Education: Bachelor’s degree in Finance, Engineering, Data Science, Statistics, Computer Science, or a related field.
Skills: Proficiency in identifying patterns and anomalies in behavioral and transactional data.
Technical Knowledge: Understanding of fraud typologies (identity fraud, shell entities, document manipulation) and familiarity with querying/visualization tools.
Collaboration: Ability to work across teams (Product, Risk, Engineering) and communicate recommendations clearly to stakeholders.
Bonus Point
Experience in credit fraud or trust & safety analytics.
Work history involving device data, behavioral signals, or real-time monitoring tools.
Experience contributing to fraud models or scoring systems.
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