Evans Kibet

Key Skills

Software

Scale AI

Remotasks

Top Subject Matter

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Top Data Types

Image

Top Label Types

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Freelancer Overview

I am a detail-oriented final-year Applied Computer Science student with hands-on experience in data entry, document preparation, and digital record organization during my attachment at a government agency. I am skilled in using Microsoft Office, Google Workspace, and basic CRM tools to ensure data accuracy and integrity. My academic background includes practical projects in web and mobile development, where I emphasized precision, ethical data handling, and structured programming. I am fluent in both Swahili and English, enabling me to work on multilingual data annotation and translation tasks. I am passionate about leveraging my technical and analytical skills to support high-quality data labeling, annotation, and AI training data projects, with a strong commitment to detail, reliability, and timely delivery.

Labeling Experience

Data Annotation Specialist (Freelance / Platform Contributor)

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As a Data Annotation Specialist, I annotated and labeled over 150,000 data points across image/object detection, text, and LLM datasets. I specialized in nuanced tasks such as multilingual NER, sentiment analysis, RLHF preference ranking, and safety content flagging. My responsibilities included quality auditing, guideline improvement contributions, and handling edge cases in real-world data. • Achieved over 98% accuracy on diverse annotation tasks. • Maintained high inter-annotator agreement scores above 0.92 Cohen’s Kappa. • Adapted to complex guideline interpretation and frequent schema updates. • Utilized leading industry platforms for efficient remote annotation.

As a Data Annotation Specialist, I annotated and labeled over 150,000 data points across image/object detection, text, and LLM datasets. I specialized in nuanced tasks such as multilingual NER, sentiment analysis, RLHF preference ranking, and safety content flagging. My responsibilities included quality auditing, guideline improvement contributions, and handling edge cases in real-world data. • Achieved over 98% accuracy on diverse annotation tasks. • Maintained high inter-annotator agreement scores above 0.92 Cohen’s Kappa. • Adapted to complex guideline interpretation and frequent schema updates. • Utilized leading industry platforms for efficient remote annotation.

2022

Junior Data Labeler / AI Training Contributor

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As a Junior Data Labeler and AI Training Contributor, I labeled over 50,000 instances in computer vision and NLP projects. My duties involved bounding boxes, polygons, and classification tasks while collaborating on dataset curation for autonomous systems. I adapted rapidly to new schemas and tools, maintaining consistent accuracy above 97% and ensuring high-quality deliverables. • Participated in chat model fine-tuning and data preparation. • Helped reduce quality escalations through careful annotation. • Contributed to both vision and NLP project pipelines. • Leveraged multiple annotation tools to meet project requirements.

As a Junior Data Labeler and AI Training Contributor, I labeled over 50,000 instances in computer vision and NLP projects. My duties involved bounding boxes, polygons, and classification tasks while collaborating on dataset curation for autonomous systems. I adapted rapidly to new schemas and tools, maintaining consistent accuracy above 97% and ensuring high-quality deliverables. • Participated in chat model fine-tuning and data preparation. • Helped reduce quality escalations through careful annotation. • Contributed to both vision and NLP project pipelines. • Leveraged multiple annotation tools to meet project requirements.

2021 - 2022

Education

Work History