Caroline Thungu

CAROLINE NJERI THUNGU Location: Nairobi Kenya Professional Summary Detail-oriented and tech-savvy Data Labeling Specialist with 2+ years of experience in annotating and labeling datasets for machine learning and computer vision projects. Adept at maintaining high accuracy under tight deadlines, collaborating with crossfunctional teams, and using annotation tools like CVAT, Labelbox, and Scale AI. Proven ability to deliver quality data for training AI systems in NLP, image, video, and audio formats. Core Competencies • Data Annotation & Tagging • Image, Video & Text Labeling • Quality Control & Review • CVAT, Labelbox, Scale AI, SuperAnnotate • Basic Python & JSON • Communication & Collaboration • Attention to Detail • Agile Workflow Understanding Professional Experience Data Labeling Specialist Appen – Remote July 2022 – January 2024 • Labeled 30,000+ images and text data for computer vision and NLP projects using Labelbox and internal tools. • Conducted QA reviews on peer annotations to ensure consistency and accuracy, achieving 98% review approval. • Followed strict annotation guidelines to maintain project alignment and reduced rework by 20%. • Collaborated with ML engineers to clarify labeling schema and resolve edge cases. Data Annotation Intern Scale AI – Remote Jan 2021 – June 2022 • Supported multiple short-term labeling projects across text and image domains. • Used internal tooling for bounding boxes, semantic segmentation, and named entity recognition (NER). • Participated in weekly performance reviews and consistently met productivity benchmarks. Education Bsc Statistics and programming Kenyatta University 2019 Certifications • Coursera: AI For Everyone by Andrew Ng • Udemy: Data Labeling for Machine Learning Technical Tools CVAT, Labelbox, SuperAnnotate, Scale AI, Amazon SageMaker Ground Truth Python (basic), JSON, Excel, Jupyter (beginner)