Key Skills

Software

Appen

Clickworker

Dataloop

Mindrift

OneForma

Telus

Top Subject Matter

Retail and E-commerce: Data labeling for product recognition and customer behavior analysis

Social Media Analysis: Data collection and evaluation for social media platforms.

Search Engine Evaluation: Search judging and analytics for optimizing search engine performance.

Top Data Types

Image

Text

Video

Top Task Types

Classification

Data Collection

Evaluation Rating

Mapping

Prompt Response Writing SFT

Freelancer Overview

With extensive experience in data labeling and AI training, I specialize in social media analysis and image annotation. My background includes significant roles with Appen, OneForma, and Telus, where I refined my skills in transforming raw data into actionable insights. I’ve contributed to prominent projects such as OGDEN, UOLO, US RATER, and TOUCHET, working across several platforms to enhance model accuracy and performance. Key qualifications include proficiency in AI and machine learning frameworks, a deep understanding of data annotation tools, and a proven track record of driving successful outcomes in complex data environments. My ability to adapt to diverse data requirements and deliver high-quality labeled datasets has consistently supported the advancement of AI training projects.

Labeling Experience

Search Engine Rater

TelusTextClassificationText Generation

Project Raters aims to enhance search engine accuracy by evaluating user queries and their results. My role involved labeling search results for relevance and accuracy, working on a large volume of queries across various topics. The project adhered to strict quality measures, ensuring results met relevance criteria and improved search algorithm performance. Regular quality checks and adherence to project guidelines were key to maintaining high standards.

Project Raters aims to enhance search engine accuracy by evaluating user queries and their results. My role involved labeling search results for relevance and accuracy, working on a large volume of queries across various topics. The project adhered to strict quality measures, ensuring results met relevance criteria and improved search algorithm performance. Regular quality checks and adherence to project guidelines were key to maintaining high standards.

2020 - 2021

Uolo

AppenImageObject DetectionEvaluation Rating

Project UOLO focuses on removing false news from the web by evaluating and classifying news articles on Socials. Data labeling tasks include assessing content accuracy and verifying facts. The project involves a large dataset with numerous contributors. Quality measures include strict guidelines, regular audits, and continuous feedback to ensure high accuracy.

Project UOLO focuses on removing false news from the web by evaluating and classifying news articles on Socials. Data labeling tasks include assessing content accuracy and verifying facts. The project involves a large dataset with numerous contributors. Quality measures include strict guidelines, regular audits, and continuous feedback to ensure high accuracy.

2016 - 2017

Education

Work History