About Digital Divide Data (DDD)

Digital Divide Data (DDD) is a US-based non-profit, mission-driven enterprise with the goal of using technology and digital skills to bridge the divide between economically and socially marginalized youth and employment opportunities that lead to a sustainable and viable future. DDD identifies talented but underserved youth in Africa and Asia (Kenya, Cambodia, and Laos are the main centers) to enter formal employment, undergo professional training and skills development, and pursue tertiary education. Our headquarters are in New York, and we have over 1,500 employees across our operations in Kenya, Cambodia, and Laos.

●      Use a variety of software tools to mark objects, activities, events, or other items of interest in images and videos.

●      Correctly map data as per client Instructions.

●      Attach metadata (comments, markups, etc.) to video data per client requirements

●      Collaborate with the team, and ensure that annotations meet project requirements with high quality.

●      Annotate and label image and video data via computer using various internal software programs.

●      Provide constructive feedback to our internal team on tooling and processes for more efficient labeling, and to improve data quality.

●      Maintain ownership of each assignment, and respond to any changes in procedure.

●      A degree or diploma in a business-related field.

●     Must have at least 1 year of lidar mapping experience.- Lidar Segmentation skills will be an added advantage.

●      Proficient knowledge of computer systems and technologies.

●      Experience working in a BPO setting.

●      A team player and excited about being an integral part of our team.

●      A self-starter capable of working alone or in a small group.

●      Enjoys working with a fast-paced team, but is able to work at the speed projects require.

●      Self-motivated to work independently, even with minimal supervision.

●      Good communication and interpersonal skills.

●      Flexibility with regard to working hours i.e. (Day/Night shifts)