Mark Kibiru

Key Skills

Software

Remotasks

Appen

Top Subject Matter

Nlp Domain Expertise

Computer Vision

Medical Data

Top Data Types

Text

Audio

Image

Document

Top Task Types

Classification

Transcription

Freelancer Overview

Data Annotation Specialist (Contract) — Remotasks / Scale AI. Brings 1+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Remotasks, Appen, and Internal. Education includes Bachelor of Science, University of Nairobi (2020). AI-training focus includes data types such as Text and Audio and labeling workflows including Classification and Transcription.

Labeling Experience

Data Annotation Specialist (Contract) — Remotasks / Scale AI

RemotasksTextClassification

As a Data Annotation Specialist at Remotasks/Scale AI, I managed annotation tasks in NLP, computer vision, and RLHF projects for diverse AI clients. My work included labeling for sentiment classification, named entity recognition, and medical NLP de-identification. I consistently maintained a high quality score and contributed to project guideline improvements. • Handled over 60,000 labeling tasks including bounding boxes, polygon segmentation, and coreference chains. • Selected for a restricted clinical note de-identification project due to accuracy. • Collaborated with project leads to refine annotation guidelines. • Familiar with tools such as Remotasks, Scale AI dashboard, CVAT, and Label Studio.

As a Data Annotation Specialist at Remotasks/Scale AI, I managed annotation tasks in NLP, computer vision, and RLHF projects for diverse AI clients. My work included labeling for sentiment classification, named entity recognition, and medical NLP de-identification. I consistently maintained a high quality score and contributed to project guideline improvements. • Handled over 60,000 labeling tasks including bounding boxes, polygon segmentation, and coreference chains. • Selected for a restricted clinical note de-identification project due to accuracy. • Collaborated with project leads to refine annotation guidelines. • Familiar with tools such as Remotasks, Scale AI dashboard, CVAT, and Label Studio.

2022 - Present

Freelance Data Labeler — Appen & Clickworker

AppenAudioTranscription

As a Freelance Data Labeler for Appen and Clickworker, I completed a range of annotation projects including audio transcription and image tagging. My assignments focused on long-form transcription with an emphasis on dialect sensitivity and accurate punctuation. I was recognized for keeping a low rejection rate and proactively developed quality resources for recurring tasks. • Managed audio, text, image, and document labeling as required by different projects. • Consistently achieved a rejection rate under 1.5%. • Developed personal checklists and shared them with colleagues for improved accuracy. • Regularly assigned to high-accuracy, complex tasks by platform managers.

As a Freelance Data Labeler for Appen and Clickworker, I completed a range of annotation projects including audio transcription and image tagging. My assignments focused on long-form transcription with an emphasis on dialect sensitivity and accurate punctuation. I was recognized for keeping a low rejection rate and proactively developed quality resources for recurring tasks. • Managed audio, text, image, and document labeling as required by different projects. • Consistently achieved a rejection rate under 1.5%. • Developed personal checklists and shared them with colleagues for improved accuracy. • Regularly assigned to high-accuracy, complex tasks by platform managers.

2020 - 2022

Final Year Project — University of Nairobi

TextClassification

For my final year project at the University of Nairobi, I manually annotated a 5,000-sentence Swahili text corpus for use in text classification benchmarking. The task required careful differentiation of categories as a baseline for automated classification. The annotated corpus served as a key resource for comparing preprocessing pipelines. • Built evaluation datasets for model training and testing. • Applied annotation best practices and maintained high inter-annotator agreement. • Focused on Swahili language sources relevant to East African data projects. • Ensured consistent labeling according to research methodology.

For my final year project at the University of Nairobi, I manually annotated a 5,000-sentence Swahili text corpus for use in text classification benchmarking. The task required careful differentiation of categories as a baseline for automated classification. The annotated corpus served as a key resource for comparing preprocessing pipelines. • Built evaluation datasets for model training and testing. • Applied annotation best practices and maintained high inter-annotator agreement. • Focused on Swahili language sources relevant to East African data projects. • Ensured consistent labeling according to research methodology.

2020 - 2020

Education

Work History