Oluwafemi O.

Key Skills

Software

Other

Appen

Mindrift

Scale AI

Top Subject Matter

Machine learning model training dataset annotation

Computer vision dataset annotation

Sentiment analysis data annotation

Top Data Types

Text

Image

Document

Top Task Types

Classification

Emotion Recognition

Segmentation

Question Answering

RLHF

Fine-tuning

Text Summarization

Computer Programming/Coding

Freelancer Overview

Freelance Data Annotator (Remote). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Engineering, Federal University Oye Ekiti. AI-training focus includes data types such as Text and Image and labeling workflows including Classification and Emotion Recognition.

Labeling Experience

Freelance Data Annotator (Remote)

OtherImageClassification

Freelance Data Annotator working on image dataset labeling for machine learning training. Maintained strict compliance with labeling instructions while ensuring consistent results across projects. Performed independent work with strong attention to detail to meet deadlines and targets. • Labeled and annotated images according to predefined rules • Reviewed and validated image labels for 95%+ accuracy and consistency • Escalated quality issues when data inconsistencies were detected • Completed daily and weekly targets in a fast-paced remote environment

2023 - Present

Freelance Data Annotator (Remote)

OtherTextClassification

Freelance Data Annotator annotating and labeling text data to support machine learning model training and downstream classification tasks. Ensured annotation accuracy and consistency by reviewing and validating labeled outputs to reach 95%+ quality benchmarks. Followed labeling guidelines across multiple projects while escalating identified data inconsistencies for correction. • Labeled and categorized text samples based on project guidelines • Performed quality assurance checks and accuracy validation on annotations • Identified inconsistencies in data and raised quality issues for resolution • Met daily and weekly annotation targets in a remote workflow

2023 - Present

Annotation Practice Projects

OtherImageClassification

Annotation practice also involved categorizing images based on predefined classification rules. The effort aimed to generate consistent labeled image categories for model use. Labeling outputs were subsequently used in basic evaluation of classification quality. • Categorized images into predefined classes • Followed labeling rules to keep label definitions consistent • Supported AI training data preparation through structured labeling • Used labeled results to inform evaluation of performance

2021 - 2023

Annotation Practice Projects

OtherTextEmotion Recognition

Annotation practice included labeling sentiment data (positive, negative, neutral) for AI training and evaluation. The work focused on applying consistent classification criteria to textual inputs. Labeled outputs were used to assess AI-generated responses for accuracy and relevance. • Labeled sentiment categories for training data • Applied predefined sentiment classification rules • Evaluated AI-generated responses against expected outputs • Verified label quality for consistency

2021 - 2023

Education

Work History