Data Analyst I
BehavioSec
Would you like to be part of a team that delivers high-quality software to our customers?
Are you a visible champion with a ‘can do’ attitude and enthusiasm that inspires others?
About the Business
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, https://risk.lexisnexis.com
About the Team
You’ll join a collaborative squad that includes a Squad Lead, Business Analyst, Development Lead, Developers, and Testers. Our squad model encourages teamwork, shared responsibility, and efficient delivery—everyone contributes to achieving a common goal.
About the Role
We are seeking detail‑oriented AI Annotators to help label and validate datasets that support models used in document integrity checks, deepfake detection, presentation attack detection (PAD), and face recognition.
Your work will directly improve the accuracy, fairness, and safety of identity verification systems used around the world. This role is open to candidates from diverse backgrounds. Training is provided, and you’ll work with a supportive team that values clear communication, curiosity, and thoughtful analysis.
Responsibilities:
Accurately label multimodal data (documents, photos, videos, audio) following project guidelines.
Annotate identity‑document elements and flag potential tampering.
Label authenticity cues and documented exceptions in various document types.
Identify and mark manipulated regions in images and videos related to deepfakes or tampering.
Tag PAD and liveness indicators such as replay, print/scan, and mask‑based attacks.
Draw face bounding boxes and annotate facial features, expressions, poses, and identity‑verification cues.
Add time‑based labels to videos for frame‑level detection of spoofing or deepfake activity.
Follow and improve annotation guidelines, perform quality checks, collaborate with engineers, and meet accuracy and productivity standards.
Requirements:
0-1 years of experience
Strong attention to detail, pattern recognition, and observational skills.
Ability to stay focused on repetitive tasks while maintaining accuracy.
Basic understanding of how data annotation supports AI or computer vision models (training provided).
Comfortable using computers and able to learn web‑based annotation tools.
Clear written and verbal communication, especially when describing unusual or ambiguous examples.
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