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E

Edwin Kiprop

Freelance Data Labeler | Appen / Scale AI / Clickworker

Kenya flagNairobi, Kenya
IntermediateAppenLabelboxScale AI

Key Skills

Software

AppenAppen
LabelboxLabelbox
Scale AIScale AI
RemotasksRemotasks

Top Subject Matter

AI Model Training
Linguistic Analysis
Medical Support Data

Top Data Types

AudioAudio
ImageImage
TextText
DocumentDocument

Top Task Types

RLHF
Classification
Entity Ner Classification

Freelancer Overview

Freelance Data Labeler | Appen / Scale AI / Clickworker. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Appen. Education includes Bachelor of Arts, Multimedia University (2025). AI-training focus includes data types such as Text and labeling workflows including RLHF.

IntermediateEnglish

Labeling Experience

Appen

Freelance Data Labeler | Appen / Scale AI / Clickworker

AppenTextRLHF
As a Freelance Data Labeler, I specialized in labeling and annotating large volumes of text prompts for preference modeling and reinforcement learning from human feedback. I maintained a 98.4% inter-rater agreement and consistently exceeded quality and throughput benchmarks in technical model training. My responsibilities involved complex linguistic judgments, edge-case flagging, and rapid adaptation to varied annotation guidelines. • Labeled over 12,000 text prompts using multiple annotation styles and guidelines. • Developed efficient shorthand processes for ambiguity and error flagging, reducing team review times. • Achieved a weekly high throughput of 1,500+ classified tasks with a sustained audit pass rate above 97%. • Mastered and adapted to three distinct technical annotation guidelines with zero recurring violations after initial calibration.

As a Freelance Data Labeler, I specialized in labeling and annotating large volumes of text prompts for preference modeling and reinforcement learning from human feedback. I maintained a 98.4% inter-rater agreement and consistently exceeded quality and throughput benchmarks in technical model training. My responsibilities involved complex linguistic judgments, edge-case flagging, and rapid adaptation to varied annotation guidelines. • Labeled over 12,000 text prompts using multiple annotation styles and guidelines. • Developed efficient shorthand processes for ambiguity and error flagging, reducing team review times. • Achieved a weekly high throughput of 1,500+ classified tasks with a sustained audit pass rate above 97%. • Mastered and adapted to three distinct technical annotation guidelines with zero recurring violations after initial calibration.

2023 - Present

Education

M

Multimedia University

Bachelor of Arts, Communication

Bachelor of Arts
2021 - 2025

Work History

F

Faraja Cancer Support

Data Quality & Compliance Lead

Nairobi
2021 - 2023
F

Faraja Cancer Support

Administrative & Data Coordinator

Nairobi
2019 - 2021