Mustafa Durmus

Key Skills

Software

Appen

Clickworker

OneForma

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Video

Top Label Types

Entity Ner Classification

Translation Localization

Evaluation Rating

Audio Recording

Transcription

Freelancer Overview

I have several years of hands-on experience in data annotation, image labeling, and transcription for both English and Turkish languages. My work with companies like OneForma and Appen has allowed me to specialize in accurately labeling images, annotating data for AI training, and evaluating the quality of social media and map content. I am skilled in data entry, translation, and transcription, with a strong attention to detail and a focus on cultural sensitivity. I continually stay updated on the latest tools and trends in machine learning and data analysis, and I enjoy sharing my knowledge to help improve team performance. My background also includes article writing and digital marketing, giving me a broad understanding of content relevance and quality assessment in various domains.

Labeling Experience

Data Annotation Specialist

OneformaTextEntity Ner ClassificationTranslation Localization

Conducted translation QA and data annotation for Turkish-English texts, including error categorization (accuracy, fluency, terminology, style, locale) and acceptability scoring (0–100). Ensured high-quality labeled data for AI training and linguistic evaluation. "Performed detailed data labeling and annotation for medical, legal, and technical texts. Tasks included source string validation, target span selection, error tagging, and scoring translations to support AI language model development." "Specialized in linguistic QA and annotation projects: identifying translation errors, categorizing issues, and providing structured scoring to improve machine learning datasets and translation quality."

Conducted translation QA and data annotation for Turkish-English texts, including error categorization (accuracy, fluency, terminology, style, locale) and acceptability scoring (0–100). Ensured high-quality labeled data for AI training and linguistic evaluation. "Performed detailed data labeling and annotation for medical, legal, and technical texts. Tasks included source string validation, target span selection, error tagging, and scoring translations to support AI language model development." "Specialized in linguistic QA and annotation projects: identifying translation errors, categorizing issues, and providing structured scoring to improve machine learning datasets and translation quality."

2020 - 2025

Education

Work History