Charity N.

Key Skills

Software

Other

Don't disclose

Appen

Clickworker

OneForma

Top Subject Matter

Household surveys for development projects (agriculture, food economics)

Household surveys for restoration and livelihoods project

Agricultural market systems research and fertilizer assessment (households, farmers, stakeholders)

Top Data Types

Text

Document

Image

Video

Audio

Top Task Types

Data Collection

Bounding Box

Entity (NER) Classification

Classification

Transcription

Freelancer Overview

Data Annotator – Telus AI International (PhotosGT Project). Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Don't disclose, Appen, and Clickworker. Education includes Bachelor of Science, Maasai Mara University (2018). AI-training focus includes data types such as Image, Text, and Video and labeling workflows including Bounding Box, Entity (NER) Classification, and Classification.

Labeling Experience

Enumerator — Kula Vyema Centre of Food Economics (Oct 2022–Mar 2026)

OtherTextData Collection

Served as an enumerator supporting large-scale household data collection for multiple development projects. Conducted field interviews and ensured data quality by submitting accurate and complete records within deadlines. Participated in enumerator training and coordinated field teams across counties to follow data collection protocols.• Conducted household survey interviews using ODK, Kobo Collect, and SurveyCTO• Collected qualitative and quantitative survey responses for development project monitoring• Ensured high-quality, accurate, and complete data submission within deadlines• Supported coordination of field teams across multiple counties

2022 - 2026

Data Annotator – Telus AI International (PhotosGT Project)

Don't discloseImageBounding Box

Contributed to the PhotosGT image annotation work by performing image annotation with bounding box labeling and metadata verification for AI training datasets. Reviewed and fact-checked labeled data to ensure it matched project guidelines, including visual accuracy and consistency. Completed structured annotation tasks under strict deadlines with minimal supervision. • Performed bounding box labeling and image annotation for computer vision training • Verified metadata and ensured labeled data consistency • Conducted guideline-based fact-checking for accuracy and visual quality • Maintained high-quality output while adhering to strict project timelines

2023 - 2025

Data Annotator – Transperfect

VideoData Collection

Contributed to the Tourmaline Video Collection Project by labeling video content for computer vision training datasets. Annotated and organized email data for the Opal Email Collection Project for NLP-oriented tasks. Ensured accurate, consistent, and complete multimedia data preparation under structured project guidelines. • Labeled video content for computer vision training • Annotated and organized email data for NLP tasks • Ensured accuracy, consistency, and completeness in labeling • Followed structured guidelines for multimedia data preparation

2024 - 2024

Annotator – Clickworker

ClickworkerTextClassification

Completed micro tasks involving data labeling, web content evaluation, and tagging of English-language data based on predefined criteria. Produced consistent outputs on instruction-heavy annotation tasks within expected timeframes. Adapted quickly to new project tools and task types with minimal ramp-up time. • Verified and tagged English-language text using predefined labeling rules • Evaluated web content as part of instruction-based micro tasks • Delivered consistent, timely annotation outputs • Quickly learned and applied new project tools and task types

2024 - 2024

Content Moderator and Annotator – Appen

AppenTextEntity (NER) Classification

Worked on the Whatcom and Tansy projects involving text classification and search relevance evaluation for AI training and moderation use cases. Fact-checked and evaluated user-generated content for accuracy, bias, and contextual appropriateness. Followed complex guidelines to annotate language and assess content performance while flagging inconsistencies. • Performed text classification and search relevance evaluation • Conducted fact-checking and bias/context assessment • Annotated language based on detailed project instructions • Collaborated to flag guideline inconsistencies and improve labeling protocols

2023 - 2024

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Education

Work History