Princewill Stanford

Key Skills

Software

OneForma

Appen

CrowdSource

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Task Types

Entity (NER) Classification

Evaluation/Rating

Classification

Freelancer Overview

I am an experienced AI prompt engineer and data annotator with a strong background in NLP data labeling, quality assurance, and large-scale dataset validation. My work spans annotating and validating text for sentiment analysis, entity tagging, and classification, as well as evaluating AI-generated outputs to refine prompts and improve model accuracy. I have contributed to projects involving search engine evaluation, content categorization, and AI output assessment for platforms like OneForma, Appen, and Microsoft UHRS. My technical skills include prompt design, LLM output evaluation, and a working knowledge of HTML and CSS, which help me bridge the gap between AI systems and web-based applications. I am detail-oriented, analytical, and committed to building reliable, high-quality AI solutions.

Labeling Experience

Data Annotator & AI Evaluator

OneformaTextEntity Ner Classification

As a Data Annotator & AI Evaluator at OneForma, I annotated and validated large-scale NLP datasets. My tasks included text classification, sentiment analysis, and entity tagging while ensuring data quality. I performed quality assurance reviews to maintain high compliance standards and enhance dataset consistency. • Annotated diverse text data using strict guidelines • Conducted sentiment analysis and entity recognition • Provided feedback for prompt optimization in LLMs • Ensured data annotation accuracy and reliability

As a Data Annotator & AI Evaluator at OneForma, I annotated and validated large-scale NLP datasets. My tasks included text classification, sentiment analysis, and entity tagging while ensuring data quality. I performed quality assurance reviews to maintain high compliance standards and enhance dataset consistency. • Annotated diverse text data using strict guidelines • Conducted sentiment analysis and entity recognition • Provided feedback for prompt optimization in LLMs • Ensured data annotation accuracy and reliability

2024

AI Data Rater

AppenTextEvaluation Rating

As an AI Data Rater at Appen, I assessed the accuracy and quality of search engine results. My responsibilities included reviewing AI-generated content and applying detailed evaluation standards. I provided insights to enhance search algorithms and contributed to AI model improvement. • Evaluated text-based search and response outputs • Flagged edge cases and inaccuracies in AI results • Applied strict rating guidelines to data • Helped train models for improved relevance and accuracy

As an AI Data Rater at Appen, I assessed the accuracy and quality of search engine results. My responsibilities included reviewing AI-generated content and applying detailed evaluation standards. I provided insights to enhance search algorithms and contributed to AI model improvement. • Evaluated text-based search and response outputs • Flagged edge cases and inaccuracies in AI results • Applied strict rating guidelines to data • Helped train models for improved relevance and accuracy

2023

UHRS Judge / AI Data Contributor

CrowdsourceTextClassification

At Microsoft via the UHRS Platform, I completed micro-task annotations and validated textual and web data. Tasks included evaluating search results, advertisements, and web pages for content categorization and quality. I ensured detailed and high-volume task completion through systematic annotation and verification. • Categorized and verified web content • Performed annotation of advertisements and search data • Delivered quality judgments on diverse tasks • Maintained consistency and accuracy across large datasets

At Microsoft via the UHRS Platform, I completed micro-task annotations and validated textual and web data. Tasks included evaluating search results, advertisements, and web pages for content categorization and quality. I ensured detailed and high-volume task completion through systematic annotation and verification. • Categorized and verified web content • Performed annotation of advertisements and search data • Delivered quality judgments on diverse tasks • Maintained consistency and accuracy across large datasets

2022 - 2023

Education

Work History