Kungu Duncan

Detail-oriented Data Annotation Specialist with 3+ years of experience delivering high-quality labeled datasets for machine learning and computer vision applications. Skilled in image and video annotation using CVAT and similar tools. Proven track record of achieving over 98% annotation accuracy while meeting tight deadlines in fast-paced remote environments.

Data Annotation Specialist - Remotask - Remote

(2023-01)

• Annotated 120,000+ images and video frames for object detection and segmentation projects.
• Achieved and maintained 98–99% annotation accuracy, consistently exceeding quality benchmarks.
• Reduced annotation errors by 25% through rigorous quality control and guideline adherence.
• Completed tasks 15% faster than average turnaround time, meeting all project deadlines.
• Collaborated with distributed teams of annotators, reviewers, and project managers across multiple projects.
• Performed preprocessing tasks including resizing, formatting, and dataset organization.

AI Data Annotator / Contributor - Outlier - Remote

(2022-06 - 2022-12)

• Labeled and validated 50,000+ data samples for AI model training and evaluation.
• Conducted peer reviews, improving overall dataset quality scores by 20%.
• Maintained consistent adherence to annotation guidelines, ensuring uniform labeling across datasets.
• Assisted in optimizing workflows, reducing annotation time per task by 10–15%.
• Delivered high-quality outputs within strict deadlines across multiple concurrent projects.

Bachelor of Science - Actuarial Science - Jomo Kenyatta University of Agriculture and Technology (JKUAT)