Fraud Analyst

Summary

Join Ocrolus's fast-growing AI-focused fraud team and play a pivotal role in strengthening its Detect product by reviewing machine-generated fraud signals, identifying detection logic gaps, and recommending improvements based on real-world fraud behaviors. Collaborate with product, engineering, and ML/data science teams to ensure accurate, scalable, and trustworthy fraud detection models for financial services clients. This role requires a sharp, investigative professional with 3–5 years of document-centric fraud risk experience in fintech, lending, or banking, focusing on detecting synthetic identities and reviewing financial documents. You will contribute to model retraining, testing, and data quality initiatives, analyze edge cases, research emerging fraud techniques, and maintain a fraud knowledge base. Support customer success and operations teams by investigating escalated fraud cases and explaining system decisions. Assist in evaluating third-party fraud signal vendors and benchmarking their performance against internal systems. The position offers the opportunity to shape the future of document fraud detection and make a measurable impact on fraud prevention and trust in financial systems.

Requirements

3–5 years of experience in fraud or risk analysis, preferably in a fintech, banking, or credit/lending environment

Responsibilities

• Review machine-generated fraud signals to evaluate accuracy, false positives, and missed detections
• Design and test detection rules and thresholds for identifying document-based fraud (e.g., tampering, synthetic documents, inconsistencies)
• Validate performance of fraud detection models against known fraud patterns and client-flagged cases
• Provide domain-specific feedback on fraud trends across bank statements, paystubs, tax documents, and IDs
• Annotate and classify documents to improve supervised training datasets
• Collaborate with Product and Engineering teams to refine scoring logic, severity classification, and signal design
• Contribute to ongoing model retraining cycles, testing initiatives, and data quality initiatives
• Analyze edge cases and ambiguous documents to refine fraud detection boundaries and reduce gray zones
• Research emerging fraud techniques and document forgery trends (including AI-generated fakes) to inform system enhancements
• Maintain a fraud knowledge base, including signal definitions, fraud playbooks, and annotation guidelines
• Support customer success and operations teams by investigating escalated fraud cases and explaining system decisions
• Assist in evaluating third-party fraud signal vendors and benchmarking their performance against internal systems

Preferred Qualifications

• Exposure to Intelligent Document Processing (IDP) flows that involve tamper detection or metadata scrutiny
• Experience in working with AI/ML-driven fraud tooling, anomaly detection, and risk scoring systems across the financial ecosystem
• Synthetic identity fraud, document forgery detection, and KYC/AML procedures
• Strong understanding of financial documents such as W-2s, 1040s, paystubs, bank statements, and identity forms
• Familiarity with fraud typologies (document forgery, synthetic identity, income misrepresentation, etc.)
• Experience using fraud detection tools, case management systems, or decision engines
• Ability to interpret model outputs, scoring systems, and signal-based decisioning frameworks
• Detail-oriented with strong analytical, written, and communication skills
• Experience working with OCR, metadata forensics, or document verification tools

Benefits

• Join a fast-growing AI-focused fraud team tackling real-world financial crime
• Opportunity to shape the future of document fraud detection
• Cross-functional exposure to Product, Engineering, ML and Data Scienceke a measurable impact on fraud prevention and trust in financial systems
• We’re a team of builders, thinkers, and problem solvers who care deeply about our mission — and each other
• As a fast-growing, remote-first company, we offer an environment where you can grow your skills, take ownership of your work, and make a meaningful impact