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Strong employer brand, metro locations, and an entry-level generalist data role drive high applicant competition.
Annotation skills and basic ML familiarity transfer easily across industries.
No explicit years or mandatory certifications; basic annotation skills and attention to detail are primary filters.
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Label and validate datasets for document fraud detection, deepfake detection, presentation attack detection, and face recognition.
Ensure annotation quality by reviewing peer work, documenting edge cases, and suggesting guideline improvements.
Collaborate with machine learning engineers and data scientists to enhance dataset quality and annotation tools.
Attention to detail and strong observational skills.
Ability to maintain accuracy in repetitive tasks.
Basic understanding of computer vision/machine learning concepts (training provided).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced with detailed manual data annotation across multiple formats (documents, images, video, audio).
Comfortable working in structured, guideline-driven tasks with high accuracy and consistency.
Able to collaborate effectively with technical teams (ML engineers and data scientists) to improve data quality.