AI Data Annotation
Image annotation project to create accurate bounding box labels for medical images.
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I am an experienced AI Trainer and Data Annotation Specialist with over 14 years in AI data labeling, quality assurance, and model evaluation across a variety of domains, including healthcare, insurance, and digital analytics. My expertise spans multimodal data annotation—working with text, images, audio, and video—as well as evaluating large language model outputs for accuracy, bias, and contextual relevance. I have consistently maintained a quality compliance score above 98% by collaborating with QA teams to refine guidelines and improve annotation accuracy. My background also includes business process optimization, KPI analysis, and remote team collaboration, ensuring efficient data operations and high-quality training data for machine learning models. I am passionate about leveraging my skills in data validation, documentation systems, and quality control to enhance AI model performance and support data-driven decision-making.
Image annotation project to create accurate bounding box labels for medical images.
Entailed text classification fot sentiment analysis, mainly labelling large volumes of text data as positive, negative or neutral based. In other cases, the labelling was beyond sentiment analysis to text classification and search relevance rating.
Master of Business Administration, Business Administration
Bachelor of Science, Computer Science
Business Operations Manager
Data Quality Analyst