Gideon Kitum

Key Skills

Software

Label Studio

CVAT

Labelbox

Snorkel AI

Prodigy

Roboflow

Top Subject Matter

Legal Services & Contract Review

Regulatory Compliance & Risk Analysis

Legal Research & Document Analysis

Top Data Types

Computer Code Programming

Text

Document

Top Task Types

Entity Ner Classification

Bounding Box

Classification

Segmentation

Object Detection

Text Generation

Question Answering

Text Summarization

Prompt Response Writing SFT

Data Collection

Computer Programming Coding

Freelancer Overview

As a trade-qualified maintenance lead, my experience in data labeling and AI training is rooted in the high-precision world of industrial IoT and CMMS (computerized maintenance management systems). I specialize in the structured categorization and labeling of complex technical datasets—specifically relating to electrical fault codes, asset performance metrics, and automated system logs. My work involves translating raw, unstructured sensor data from PLC and SCADA systems into labeled training sets for predictive maintenance models, which directly resulted in a less than 2% breakdown rate and a 37% increase in production output through improved machine learning accuracy. What sets me apart is the rare combination of technical trade expertise and administrative strategic planning. I don’t just label data; I validate its technical integrity based on international standards like IEC and OSHA. My experience includes supervising the "ground truth" verification for automated voltage regulation systems and managing technical documentation for 12kV RMU installations. This ensures that the AI models I help train are not only mathematically sound but also physically accurate for high-stakes industrial environments. I bring a meticulous "Global Standard" mindset to data quality, ensuring that every labeled point contributes to a safer, more efficient operational ecosystem.

Labeling Experience

Education

Work History