Bravian Nyamosi

Key Skills

Software

Scale AI

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

Image

Audio

Video

Top Label Types

Bounding Box

Audio Recording

Question Answering

Data Collection

Freelancer Overview

I have hands-on experience contributing to AI training data through accurate data labeling, annotation, and quality review across multiple task types. My work includes text classification, sentiment analysis, entity recognition, content moderation, and prompt–response evaluation, where precision and consistency are essential. I am comfortable following detailed annotation guidelines, adapting quickly to new task instructions, and maintaining high accuracy under tight deadlines. What sets me apart is my strong attention to detail, analytical thinking, and reliability in delivering clean, well-structured datasets that directly improve model performance. I understand how high-quality annotations influence model behavior, bias reduction, and overall AI reliability. With a background in digital tools, remote collaboration, and fast learning, I consistently meet quality benchmarks while scaling across diverse data domains and AI training objectives.

Labeling Experience

Silencio Freelance Project

Internal Proprietary ToolingAudioAudio Recording

For audio contribution, I was tasked with recording short voice clips, read scripts for text-to-speech (TTS) training, or capture everyday environmental sounds.

For audio contribution, I was tasked with recording short voice clips, read scripts for text-to-speech (TTS) training, or capture everyday environmental sounds.

2025

Video Labeller

Scale AIVideoQuestion AnsweringData Collection

I worked on a sports video labeling project covering the 2021–2022 English Premier League season, focused on annotating 12 full-match football videos for AI training purposes. The scope included temporal event labeling such as goals, shots on target, passes, fouls, offsides, set pieces, substitutions, and ball possession changes, as well as player and team identification during key sequences. Annotations were performed using frame-accurate tools and predefined taxonomies to ensure consistency across matches. Quality was maintained through strict adherence to annotation guidelines, timestamp precision checks, and multi-pass reviews of labelled segments. Each video underwent self-review and peer validation to minimize missed events and misclassifications, with feedback loops used to correct inconsistencies. Accuracy, consistency, and completeness were the primary quality metrics, ensuring the dataset was reliable for downstream sports analytics and computer vision models.

I worked on a sports video labeling project covering the 2021–2022 English Premier League season, focused on annotating 12 full-match football videos for AI training purposes. The scope included temporal event labeling such as goals, shots on target, passes, fouls, offsides, set pieces, substitutions, and ball possession changes, as well as player and team identification during key sequences. Annotations were performed using frame-accurate tools and predefined taxonomies to ensure consistency across matches. Quality was maintained through strict adherence to annotation guidelines, timestamp precision checks, and multi-pass reviews of labelled segments. Each video underwent self-review and peer validation to minimize missed events and misclassifications, with feedback loops used to correct inconsistencies. Accuracy, consistency, and completeness were the primary quality metrics, ensuring the dataset was reliable for downstream sports analytics and computer vision models.

2021 - 2022

Freelance Remotask Project

Scale AIImageBounding Box

I was tasked with drawing bounding boxes around objects like cars, pedestrians, or stop signs in images to help an AI model recognize and locate them for ease of autonomous vehicle mobility.

I was tasked with drawing bounding boxes around objects like cars, pedestrians, or stop signs in images to help an AI model recognize and locate them for ease of autonomous vehicle mobility.

2021 - 2021

Education

Work History