Omogbolahan A.

Key Skills

Software

Mindrift

Other

Top Subject Matter

AI model training and LLM response improvement

User research data collection for AI/UX insights

Survey-based data collection for research datasets

Top Data Types

Text

Document

Video

Top Task Types

Data Collection

Freelancer Overview

Generalist AI Trainer (Mindrift). Professional background includes roles such as User & Research Specialist and Survey Specialist. Core strengths include Mindrift, Other, and Prolific. Education includes Bachelor of Science, Obafemi Awolowo University (2024). AI-training focus includes data types such as Text and Document and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

Survey Specialist (Prolific)

TextData Collection

Completed academic and commercial research surveys with precision to support generation of valid datasets. Maintained high approval ratings by following study instructions and providing thoughtful, accurate responses. Participated across diverse topics such as behavioral economics, psychology, and consumer studies. • Survey response data collection • Instruction-following to maintain approval ratings • Topic coverage across behavioral economics and psychology • Reliable submission of accurate responses

2024 - Present

User & Research Specialist (dscout)

OtherDocumentData Collection

Contributed to user research missions by producing structured qualitative and quantitative insights for client research teams. Documented user behaviors, pain points, and experiences through diary studies and in-context research tasks. Submitted written responses and video deliverables aligned with researcher guidelines and deadlines. • Diary study documentation and in-context research tasks • Capture of user behaviors, pain points, and experiences • Written and video research submissions • Mission quality and reliability

2024 - Present

Generalist AI Trainer (Mindrift)

MindriftText

Provided high-quality annotations, prompts, and feedback to train and iteratively improve AI model responses across multiple task domains. Evaluated outputs for accuracy, tone, reasoning, and safety to support refinement cycles and quality thresholds. Collaborated on prompt engineering to enhance response quality and consistency in a fast-paced remote environment. • AI model annotation and prompt-writing • Output evaluation across accuracy, tone, reasoning, and safety • Prompt engineering support for response consistency • Maintained high throughput and quality standards

2024 - Present

Education

Work History