Emilio Njagi

Key Skills

Software

AWS SageMaker

Appen

Clickworker

CVAT

Mindrift

OneForma

Snorkel AI

Internal/Proprietary Tooling

Top Subject Matter

LLM evaluation

audio Dta collection

text classification

Top Data Types

Image

Text

Video

Top Task Types

Classification

Computer Programming Coding

Data Collection

Evaluation Rating

Question Answering

Freelancer Overview

AI Trainer and Data Analyst with a strong foundation in finance and hands-on experience in large language model (LLM) optimization, data annotation, and performance evaluation. Proven record in refining AI-generated outputs, improving factual accuracy, and optimizing model efficiency through prompt engineering and cache management. Experienced in cloud platforms (AWS Bedrock, Vertex AI) and financial data analytics. Currently focused on integrating AI model evaluation and financial analytics to strengthen business intelligence and data-driven decision-making

Labeling Experience

Data Analyst – Finance & Research Projects

CVATDocumentEntity Ner ClassificationClassification

Processed and cleaned 10,000+ financial and academic records, improving data usability for research and AI modeling.  Built Power BI dashboards and Excel visualizations to monitor project KPIs and AI dataset metrics.  Supported data-driven decision-making by producing financial forecasts and budget trend reports.  Assisted in feature extraction for machine learning pipelines, supporting AI model preparation.

Processed and cleaned 10,000+ financial and academic records, improving data usability for research and AI modeling.  Built Power BI dashboards and Excel visualizations to monitor project KPIs and AI dataset metrics.  Supported data-driven decision-making by producing financial forecasts and budget trend reports.  Assisted in feature extraction for machine learning pipelines, supporting AI model preparation.

2023 - 2024

Data Annotation Specialist & Reviewer

Internal Proprietary ToolingDocumentFine TuningEvaluation Rating

Annotated and validated 1,000+ datasets (text, image, video) with a 99.9% accuracy rate.  Conducted multilingual annotation and red teaming tasks to improve LLM ethical behavior and response quality.  Identified 500+ edge cases, refining dataset labeling protocols and boosting model learning efficiency.  Collaborated with QA leads to review project outputs and ensure compliance with annotation guidelines

Annotated and validated 1,000+ datasets (text, image, video) with a 99.9% accuracy rate.  Conducted multilingual annotation and red teaming tasks to improve LLM ethical behavior and response quality.  Identified 500+ edge cases, refining dataset labeling protocols and boosting model learning efficiency.  Collaborated with QA leads to review project outputs and ensure compliance with annotation guidelines

2023 - 2024

Education

Work History