Isaac W.

Key Skills

Software

Scale AI

iMerit

Data Annotation Tech

Top Subject Matter

Machine learning model training data annotation (NLP tasks: sentiment, intent, NER)

English language instruction and academic support (remote tutoring)

Top Data Types

Text

Image

Document

Top Task Types

Entity (NER) Classification

Question Answering

Text Summarization

Freelancer Overview

AI Data Annotator (Freelance) — Remote Platforms (Scale AI). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Scale AI and Don't disclose. Education includes Bachelor of Arts, University of Nairobi. AI-training focus includes data types such as Text and labeling workflows including Entity (NER) Classification and Question Answering.

Labeling Experience

Online English Tutor (Freelance, Remote)

Don't discloseTextQuestion Answering

Provided one-on-one online English tutoring via Zoom and Google Meet, using structured lesson plans and progress reporting to support student learning outcomes. While not an explicit labeling job, the tutoring activity involved reading and evaluation of student language and feedback cycles. The role required clear communication, careful assessment of student struggles, and iterative instruction based on performance. • Taught English language and literature through remote sessions. • Created lesson plans tailored to each student’s specific difficulties. • Sent written progress reports to parents after each session cycle. • Evaluated student work to guide subsequent instruction.

2023 - Present

AI Data Annotator (Freelance) — Remote Platforms (Scale AI)

Scale AITextEntity (NER) Classification

Served as a freelance AI data annotator on remote platforms, labeling text (and other modalities referenced) to support training of machine learning models. Performed sentiment analysis, intent classification, and named entity identification on large volumes while following task instructions precisely. Maintained quality scores above 98% through careful instruction review and peer review checks. • Labeled text data for sentiment, intent, and named entities. • Flagged ambiguous cases instead of guessing. • Used peer review queues to catch inconsistencies early. • Consistently achieved quality scores above 98%.

2024 - 2025

Education

Work History