Daniel O.

Key Skills

Software

Telus

Other

Top Subject Matter

Social content moderation

cultural sensitivity

and policy compliance evaluation

Top Data Types

Text

Video

Audio

Image

Document

Top Task Types

Bounding Box

Point/Key Point

Text Generation

Object Detection

Fine-tuning

Prompt + Response Writing (SFT)

Evaluation/Rating

Freelancer Overview

TELUS International AI — Remote (Content evaluation/rating for AI training). Core strengths include Telus and Other. Education includes Bachelor of Engineering, N/A. AI-training focus includes data types such as Text, Video, and Audio and labeling workflows including Evaluation, Rating, and Sentiment.

Labeling Experience

English-Igbo Phrase Matching Project — Remote (Translation pairing for chatbot dataset)

OtherText

Matched translation pairs for a multilingual chatbot training dataset to improve translation and intent understanding. Coordinated alignment of bilingual phrase pairs for use in chatbot model training. Ensured the matched pairs followed the dataset’s language pairing expectations. • Matched translation pairs for multilingual chatbot training • Supported bilingual alignment for conversational AI data • Contributed to dataset validation through correct pairing • Worked remotely with the Imo hub team

Present

Igbo Text-to-Speech Silencio — Remote (Dialect annotation for speech models)

OtherAudio

Participated in annotation of local dialects to support speech AI model training. Worked with language-specific data to improve coverage for the speech dataset. Contributed to building labeled resources aligned with the project’s requirements. • Annotated local dialect speech content for speech AI models • Supported training data preparation for multilingual/localized speech • Applied annotation guidance for dialect-specific labeling • Collaborated with a remote team based in the FUTO environment

Present

Atlas Video Analysis — Remote (Video sentiment tagging)

OtherVideo

Tagged a large collection of videos for sentiment using custom labeling guidelines for an AI video analysis project. Applied consistent annotation criteria across thousands of items to support sentiment modeling. Ensured labeled outputs matched the project’s structured instruction set. • Tagged 5,000+ videos for sentiment • Followed custom labeling guidelines for sentiment labels • Produced consistent annotations for video analysis dataset • Supported remote team workflows for dataset creation

Present

TELUS International AI — Remote (Content evaluation/rating for AI training)

TelusText

Evaluated user-generated social content for relevance, tone, and policy compliance while supporting AI training quality. Assessed cultural sensitivity in both ads and organic posts to reduce violations and improve dataset consistency. Delivered high-volume ratings with strong accuracy to help downstream machine learning performance. • Rated over 800 items per week at 98.6% accuracy • Evaluated content relevance and tone • Ensured adherence to policy and guideline requirements • Identified and reduced flagged cultural-sensitivity issues by 22%

Present

Education

Work History