Cris Kamaar

Key Skills

Software

iMerit

Labelbox

Label Studio

Other

Top Subject Matter

AI/ML Training Data

Business/AI Data Analytics

Sentiment Analysis/NLP

Top Data Types

Text

Image

Top Task Types

Classification

Freelancer Overview

Data Annotation Specialist — iMerit. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include iMerit, Labelbox, and Label Studio. Education includes Bachelor of Science, Taita Taveta University (2018). AI-training focus includes data types such as Text and labeling workflows including Classification.

Labeling Experience

Data Annotation Specialist — iMerit

ImeritTextClassification

As a Data Annotation Specialist at iMerit, I contributed to the preparation and labeling of high-quality datasets for AI and machine learning workflows. My responsibilities included ensuring the precision and consistency of annotations, addressing edge cases, and refining operational processes. I utilized Python and advanced annotation tools to handle a variety of data labeling tasks effectively. • Delivered accurate and consistent annotations for text data. • Improved workflows and handled challenging annotation cases. • Applied quality assurance techniques throughout. • Used iMerit internal and external annotation tools.

As a Data Annotation Specialist at iMerit, I contributed to the preparation and labeling of high-quality datasets for AI and machine learning workflows. My responsibilities included ensuring the precision and consistency of annotations, addressing edge cases, and refining operational processes. I utilized Python and advanced annotation tools to handle a variety of data labeling tasks effectively. • Delivered accurate and consistent annotations for text data. • Improved workflows and handled challenging annotation cases. • Applied quality assurance techniques throughout. • Used iMerit internal and external annotation tools.

2026 - Present

Annotation & QA Specialist — Aya Data

LabelboxTextClassification

At Aya Data, I worked as an Annotation & QA Specialist, focusing on maintaining exceptional accuracy standards across labeled datasets. My primary duties involved text annotation, quality assurance checks, and thorough documentation of labeling decisions. Utilizing tools such as Labelbox and Label Studio, I ensured data integrity and workflow efficiency. • Achieved over 99% annotation accuracy on text datasets. • Performed quality assurance and documented decisions. • Ensured consistency and reliability in final datasets. • Collaborated remotely using advanced annotation tools.

At Aya Data, I worked as an Annotation & QA Specialist, focusing on maintaining exceptional accuracy standards across labeled datasets. My primary duties involved text annotation, quality assurance checks, and thorough documentation of labeling decisions. Utilizing tools such as Labelbox and Label Studio, I ensured data integrity and workflow efficiency. • Achieved over 99% annotation accuracy on text datasets. • Performed quality assurance and documented decisions. • Ensured consistency and reliability in final datasets. • Collaborated remotely using advanced annotation tools.

2025 - 2026

Data Annotation Specialist — Pareto.AI

Label StudioTextClassification

During my tenure as a Data Annotation Specialist at Pareto.AI, I was responsible for high-volume annotation of text datasets for AI system development. My work focused on efficiently labeling large batches of data while applying robust validation techniques to improve annotation consistency. I primarily used Label Studio and related internal tools in this role. • Completed high-volume annotation tasks on text data. • Increased consistency through validation processes. • Supported AI training via accurate labeling. • Used internal and external annotation software.

During my tenure as a Data Annotation Specialist at Pareto.AI, I was responsible for high-volume annotation of text datasets for AI system development. My work focused on efficiently labeling large batches of data while applying robust validation techniques to improve annotation consistency. I primarily used Label Studio and related internal tools in this role. • Completed high-volume annotation tasks on text data. • Increased consistency through validation processes. • Supported AI training via accurate labeling. • Used internal and external annotation software.

2025 - 2025

Data Analyst & Annotation Specialist — Prospector LLC

OtherTextClassification

As a Data Analyst & Annotation Specialist at Prospector LLC, I managed the annotation of over 50,000 text data points, alongside data cleaning and dashboard development. My key contributions involved labeling datasets for downstream AI/ML applications and maintaining high standards of data integrity. The primary tools used included Excel, Python (Pandas), and internal annotation platforms. • Labeled over 50,000 text data points. • Cleaned datasets and contributed to data workflow improvements. • Utilized Python and Excel for annotation and QA tasks. • Maintained accurate records of annotation activities.

As a Data Analyst & Annotation Specialist at Prospector LLC, I managed the annotation of over 50,000 text data points, alongside data cleaning and dashboard development. My key contributions involved labeling datasets for downstream AI/ML applications and maintaining high standards of data integrity. The primary tools used included Excel, Python (Pandas), and internal annotation platforms. • Labeled over 50,000 text data points. • Cleaned datasets and contributed to data workflow improvements. • Utilized Python and Excel for annotation and QA tasks. • Maintained accurate records of annotation activities.

2021 - 2024

Sentiment Analysis Project (Python)

OtherTextClassification

In a Sentiment Analysis project using Python, I collected, cleaned, and annotated text reviews for sentiment classification. My responsibilities included labeling sentiment as positive or negative, preparing data for model training, and visualizing trends with analysis tools. Tools used included Python for data preparation and internal annotation routines. • Collected and cleaned text review data for sentiment analysis. • Labeled sentiment as positive or negative for model training. • Visualized sentiment trends using Python. • Prepared data for machine learning projects.

In a Sentiment Analysis project using Python, I collected, cleaned, and annotated text reviews for sentiment classification. My responsibilities included labeling sentiment as positive or negative, preparing data for model training, and visualizing trends with analysis tools. Tools used included Python for data preparation and internal annotation routines. • Collected and cleaned text review data for sentiment analysis. • Labeled sentiment as positive or negative for model training. • Visualized sentiment trends using Python. • Prepared data for machine learning projects.

2020 - 2021

Education

Work History