Simon Mwangi

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Top Label Types

Evaluation Rating

Red Teaming

Computer Programming Coding

Data Collection

Prompt Response Writing SFT

Freelancer Overview

With four years of software development experience, I bring strong skills in data management, data entry, and process optimization, which are highly relevant to data labeling and AI training data roles. My background includes hands-on work with Python, Django, JavaScript, and modern frameworks like React and Next.js, as well as experience with databases such as MongoDB and PostgreSQL. I have performed high-accuracy data entry, managed and maintained large datasets, and developed REST APIs to streamline data flow between applications. My experience in the medical and e-commerce domains, along with a keen attention to detail and a commitment to quality, enables me to efficiently handle, annotate, and validate data for AI and machine learning projects. I am passionate about contributing to impactful AI solutions by ensuring data quality and integrity throughout the annotation process.

Labeling Experience

AI-Assisted Data Collection, Labeling & Validation for Web-Extracted Datasets

Scale AIComputer Code ProgrammingEvaluation RatingRed Teaming

Designed and executed end-to-end data collection, labeling, and validation workflows for datasets extracted from dynamic, JavaScript-rendered websites and backend APIs. Collected large volumes of structured and semi-structured data using Python-based scraping and API pipelines, then manually and programmatically classified, normalized, and annotated entities (e.g., names, locations, pricing, categories, and transaction metadata). Applied quality control and evaluation checks to verify accuracy, consistency, and formatting prior to delivery in CSV and JSON formats. Leveraged AI/LLM-assisted prompting to accelerate data review, enrichment, and error detection while maintaining human-verified standards. This work supported automation, analytics, and AI-driven features for SaaS, e-commerce, and payment-enabled platforms, requiring strong attention to detail, independent execution, and reliable dataset delivery.

Designed and executed end-to-end data collection, labeling, and validation workflows for datasets extracted from dynamic, JavaScript-rendered websites and backend APIs. Collected large volumes of structured and semi-structured data using Python-based scraping and API pipelines, then manually and programmatically classified, normalized, and annotated entities (e.g., names, locations, pricing, categories, and transaction metadata). Applied quality control and evaluation checks to verify accuracy, consistency, and formatting prior to delivery in CSV and JSON formats. Leveraged AI/LLM-assisted prompting to accelerate data review, enrichment, and error detection while maintaining human-verified standards. This work supported automation, analytics, and AI-driven features for SaaS, e-commerce, and payment-enabled platforms, requiring strong attention to detail, independent execution, and reliable dataset delivery.

2022

Education

Work History