David Gbadamosi

Key Skills

Software

SuperAnnotate

Other

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Image

Video

Top Label Types

RLHF

Segmentation

Freelancer Overview

I am a detail-oriented data scientist with hands-on experience in data annotation, labeling, and AI model evaluation, particularly in computer vision and large language models. My background includes assessing and improving the quality of AI training data at SuperAnnotate and evaluating Python-based AI model outputs for logical consistency, correctness, and real-world alignment. I am skilled in Python, SQL, and statistical modeling, and have worked with tools such as Jupyter, Power BI, and AWS. My strengths lie in transforming raw data into actionable insights, building reproducible workflows, and applying standardized rubrics to ensure high-quality, scalable data labeling and annotation. I am passionate about supporting the development of robust AI systems through meticulous data curation and quality assessment.

Labeling Experience

Data Labeling Specialist (Video Annotation)

OtherVideoSegmentation

Worked on video data annotation projects involving temporal segmentation and event labeling. The task involved analyzing video footage and specifying all actions and activities occurring at different timestamps. Performed time-based labeling to classify behaviors, movements, and scene-level events to support computer vision model training. Used structured annotation guidelines within Atlas to ensure consistency and accuracy across datasets.

Worked on video data annotation projects involving temporal segmentation and event labeling. The task involved analyzing video footage and specifying all actions and activities occurring at different timestamps. Performed time-based labeling to classify behaviors, movements, and scene-level events to support computer vision model training. Used structured annotation guidelines within Atlas to ensure consistency and accuracy across datasets.

2025

Subject Matter Specialist (Python) – AI Model Evaluation

SuperannotateComputer Code ProgrammingRLHF

Completed an RLHF-based annotation project using SuperAnnotate, focused on evaluating and labeling Python-related outputs for AI model improvement. Reviewed model-generated responses and applied structured feedback to assess correctness, logical consistency, and task alignment. Contributed to reinforcement learning workflows by providing human feedback used to refine model performance. Maintained quality standards by following annotation guidelines and ensuring accurate evaluation of Python-based solutions.

Completed an RLHF-based annotation project using SuperAnnotate, focused on evaluating and labeling Python-related outputs for AI model improvement. Reviewed model-generated responses and applied structured feedback to assess correctness, logical consistency, and task alignment. Contributed to reinforcement learning workflows by providing human feedback used to refine model performance. Maintained quality standards by following annotation guidelines and ensuring accurate evaluation of Python-based solutions.

2025

Education

Work History