Document Analyst – Remote

About the role

We are seeking a remote Document Analyst to ensure the accuracy, authenticity, and compliance of a wide range of documents. You will play a critical part in safeguarding our operations by detecting fraud, validating data, and supporting machine‑learning model improvement.

Key responsibilities

• Analyze and validate data extracted from IDs, proof‑of‑address, financial statements, legal contracts, and medical forms.
• Identify sophisticated document fraud, including photoshopped IDs, counterfeit documents, and deep‑fake attempts.
• Apply forensic techniques to detect anomalies in security features such as holograms, watermarks, and micro‑print.
• Handle edge cases involving damaged, non‑standard, or foreign‑jurisdiction documents.
• Collaborate with Policy and Product teams to refine annotation guidelines and improve global document coverage.
• Provide structured feedback to ML engineers and data scientists on model performance and OCR errors.
• Perform quality checks on annotations and ensure high inter‑annotator agreement.
• Maintain compliance with KYC, AML, GDPR, eIDAS and other relevant regulations.
• Identify workflow improvements to reduce manual effort while preserving accuracy.

Required profile

• Minimum 3 years experience in document analysis, identity verification, KYC/AML operations, or data extraction.
• Deep knowledge of global identity, financial, and legal documents.
• Proven ability to detect advanced document fraud and biometric discrepancies.
• Experience with document verification tools, OCR software, or annotation platforms.
• Familiarity with structured data formats such as JSON, XML, or CSV.
• Strong understanding of KYC/AML frameworks and data‑privacy regulations (GDPR, CCPA).

Required skills

• OCR software
• Document verification tools
• Annotation platforms
• JSON
• XML
• CSV

What we offer

• Fully remote work with flexible hours.
• Opportunity to influence AI‑driven fraud detection systems.
• Collaborative environment with cross‑functional teams.