Adeleke Emmanuel

I’m a Detail-oriented Data Annotator with 2 years of experience in accurately labeling and categorizing diverse datasets, including images, text, and audio. I focus on building high-quality datasets for model training by applying consistent, guideline-based annotation methods.

In my current Freelance role with Appen (2023 - Present), I label and refine data using approaches such as bounding boxes, semantic segmentation, key point detection, and text classification. I also use tools like Single Review Tool (SRT) and Keikaku to label text, identify intents, and categorize responses.

I adapt quickly as the data annotation field evolves, staying flexible with new tools and technologies. I manage edge cases effectively before client escalation, ensuring the dataset output remains accurate and usable.

I bring strong written and verbal communication skills to collaborate with cross functional teams, clarify project requirements, and follow annotation instructions with care. Overall, I’m motivated by the opportunity to keep improving dataset quality and reliability for ML systems.