Francis Kamau

Key Skills

Software

AWS SageMaker

Appen

Clickworker

CloudFactory

Deep Systems

Mercor

Mindrift

OneForma

Remotasks

Scale AI

Surge AI

Telus

Labelbox

Other

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Video

Top Task Types

Computer Programming Coding

Data Collection

Entity Ner Classification

Evaluation Rating

Translation Localization

Freelancer Overview

I am an experienced data analyst and AI practitioner with over 7 years of experience in data analytics, machine learning, and AI model development. My background includes creating and deploying credit scoring and cash flow prediction models using Python, TensorFlow, and AWS, as well as managing international data teams. I bring advanced technical skills in Python, R, SQL, Tableau, and data visualization, with deep experience in data cleaning, labeling, standardization, and model evaluation. Beyond analytics, I have led Natural Language Processing (NLP) projects involving sentiment analysis, language detection, and named entity recognition using SpaCy and Hugging Face. I have also built datasets for translation and sentiment modeling, ensuring high-quality, ethically sound AI training data. My combination of technical expertise, leadership experience, and hands-on project delivery positions me to contribute effectively in building reliable and impactful AI systems.

Labeling Experience

Quality Rating and Evaluation for AI Models

TelusVideoEmotion RecognitionEvaluation Rating

Performed quality rating and evaluation tasks for AI and machine learning models. Responsibilities included assessing outputs from text, audio, and image models for accuracy, relevance, and adherence to guidelines. Provided detailed feedback to improve model performance and reduce biases. Maintained consistency and high quality through cross-checking with team members and following strict evaluation standards.

Performed quality rating and evaluation tasks for AI and machine learning models. Responsibilities included assessing outputs from text, audio, and image models for accuracy, relevance, and adherence to guidelines. Provided detailed feedback to improve model performance and reduce biases. Maintained consistency and high quality through cross-checking with team members and following strict evaluation standards.

2025

Data Annotation and Labeling for AI Training

Scale AIImageBounding BoxEntity Ner Classification

Performed data annotation and labeling across multiple modalities to support machine learning model training. Tasks included annotating text for named entities and sentiment, labeling images with bounding boxes and segmentation masks, and transcribing audio with timestamps. Ensured high-quality data by following detailed labeling guidelines, performing inter-annotator agreement checks, and conducting quality audits.

Performed data annotation and labeling across multiple modalities to support machine learning model training. Tasks included annotating text for named entities and sentiment, labeling images with bounding boxes and segmentation masks, and transcribing audio with timestamps. Ensured high-quality data by following detailed labeling guidelines, performing inter-annotator agreement checks, and conducting quality audits.

2024 - 2025

Data Annotation and Coding for AI Pipelines

OtherComputer Code ProgrammingComputer Programming CodingPrompt Response Writing SFT

In this project I performed coding and data programming tasks to support AI model training and data annotation pipelines. Developed scripts to automate data preprocessing, labeling, and validation workflows for text, image, and audio datasets. Implemented function calls, prompt-response generation, and quality checks to ensure accurate and high-quality labeled data

In this project I performed coding and data programming tasks to support AI model training and data annotation pipelines. Developed scripts to automate data preprocessing, labeling, and validation workflows for text, image, and audio datasets. Implemented function calls, prompt-response generation, and quality checks to ensure accurate and high-quality labeled data

2023 - 2025

Natural Language Data Labeling and Evaluation for NLP Model Training

LabelboxTextEntity Ner ClassificationSegmentation

Led a Natural Language Processing (NLP) data labeling initiative to build high-quality multilingual datasets for sentiment analysis, named entity recognition (NER), and translation model development. Managed and annotated text datasets used in training and evaluation of AI models, ensuring data quality, consistency, and balanced representation. Collaborated with a distributed labeling team using Appen and Labelbox, implementing Python scripts for automated validation and error detection. The labeled datasets were later used to fine-tune and evaluate AI language models for translation, sentiment detection, and chatbot response optimization.

Led a Natural Language Processing (NLP) data labeling initiative to build high-quality multilingual datasets for sentiment analysis, named entity recognition (NER), and translation model development. Managed and annotated text datasets used in training and evaluation of AI models, ensuring data quality, consistency, and balanced representation. Collaborated with a distributed labeling team using Appen and Labelbox, implementing Python scripts for automated validation and error detection. The labeled datasets were later used to fine-tune and evaluate AI language models for translation, sentiment detection, and chatbot response optimization.

2021 - 2024

Education

Work History