Maureen Kamau

Key Skills

Software

Appen

Clickworker

CloudFactory

CrowdSource

CVAT

Data Annotation Tech

Dataloop

Figure Eight

Hasty

iMerit

Labelbox

LabelImg

Label Studio

Lionbridge

Mighty AI

Mindrift

OneForma

Remotasks

Sama

Scale AI

SuperAnnotate

Toloka

V7 Labs

Top Subject Matter

Financial Documents

Construction Plans/Drawings

Autonomous Vehicles – LiDAR Data

Top Data Types

Audio

Image

Video

Document

3D Sensor

Text

Top Task Types

Bounding Box

Classification

Mapping

Polygon

Segmentation

Freelancer Overview

I am a QA Analyst and Data Annotator with over four years of experience contributing to AI training datasets. I have worked on projects involving financial document labeling, structured document review, and 3D sensor data annotation using internal proprietary tools and platforms such as Remotasks. My work includes tasks such as classification, segmentation, and quality review to ensure datasets meet strict annotation guidelines. I am detail-oriented and experienced in handling large datasets while maintaining high accuracy and consistency. My background in document analysis and data labeling allows me to support AI model training by ensuring high-quality, well-structured training data.

Labeling Experience

QA Analyst – Financial Document Labeling

DocumentClassification

As a QA Analyst at Two Dots, I classified and labeled financial documents to support accurate document processing workflows. I ensured regulatory compliance and high accuracy through meticulous categorization and tagging. By refining labeling procedures, I helped improve document reliability and interpretation. • Refined standards and introduced efficient processes for labeling financial documents. • Conducted comprehensive quality assurance checks to maintain high accuracy. • Collaborated with team members to solve complex labeling challenges. • Achieved faster turnaround and improved productivity through workflow optimization.

As a QA Analyst at Two Dots, I classified and labeled financial documents to support accurate document processing workflows. I ensured regulatory compliance and high accuracy through meticulous categorization and tagging. By refining labeling procedures, I helped improve document reliability and interpretation. • Refined standards and introduced efficient processes for labeling financial documents. • Conducted comprehensive quality assurance checks to maintain high accuracy. • Collaborated with team members to solve complex labeling challenges. • Achieved faster turnaround and improved productivity through workflow optimization.

2023 - Present

Audio Transcription and Classification for Voice AI Training

CloudfactoryAudioSegmentationClassification

At CloudFactory, I worked on a large-scale audio transcription and classification project for a client developing AI-powered voice assistants. The task involved: Transcribing short conversational audio clips into clean, readable text (verbatim and non-verbatim) Removing disfluencies, correcting grammar, and standardizing formatting per strict guidelines Classifying the speaker’s intent, tone, and emotional state Segmenting audio into logical units (e.g., turns, sentences) Performing QA audits and flagging ambiguous or poor-quality audio Adhering to accuracy standards above 98% and tight deadlines across multiple batches The project covered over 50,000 audio clips and was completed by a team of trained annotators, where I also served as a peer reviewer and informal team lead for quality improvement initiatives.

At CloudFactory, I worked on a large-scale audio transcription and classification project for a client developing AI-powered voice assistants. The task involved: Transcribing short conversational audio clips into clean, readable text (verbatim and non-verbatim) Removing disfluencies, correcting grammar, and standardizing formatting per strict guidelines Classifying the speaker’s intent, tone, and emotional state Segmenting audio into logical units (e.g., turns, sentences) Performing QA audits and flagging ambiguous or poor-quality audio Adhering to accuracy standards above 98% and tight deadlines across multiple batches The project covered over 50,000 audio clips and was completed by a team of trained annotators, where I also served as a peer reviewer and informal team lead for quality improvement initiatives.

2019

Data Annotation Specialist – Construction AI

DocumentClassification

As a Data Annotation Specialist at SketchDeck.ai, I annotated construction plans to train an AI model for construction understanding. I labeled varied plan elements to enhance information extraction accuracy by the AI. My tasks contributed significantly to high-quality datasets for machine learning and AI systems. • Led diverse data annotation projects for machine learning applications. • Managed project timelines and coordinated annotation team workflows. • Developed annotation guidelines and applied quality control measures. • Trained and mentored teams to improve annotation quality and efficiency.

As a Data Annotation Specialist at SketchDeck.ai, I annotated construction plans to train an AI model for construction understanding. I labeled varied plan elements to enhance information extraction accuracy by the AI. My tasks contributed significantly to high-quality datasets for machine learning and AI systems. • Led diverse data annotation projects for machine learning applications. • Managed project timelines and coordinated annotation team workflows. • Developed annotation guidelines and applied quality control measures. • Trained and mentored teams to improve annotation quality and efficiency.

2022 - 2023

videoHigh-Precision Video Annotation for Object Detection & Action Recognition

AppenVideoBounding BoxPolygon

This project involved detailed video annotation for computer vision models used in autonomous vehicle training and smart surveillance systems. I was responsible for accurately identifying and labeling multiple object classes (e.g., pedestrians, vehicles, road signs) across video frames using bounding boxes and polygons. Tasks included: Frame-by-frame tracking of objects across scenes Annotating human actions for behavior analysis Quality assurance reviews to maintain >97% annotation accuracy Strict adherence to complex labeling guidelines and edge-case handling Collaborating with QA and ML engineers to optimize annotation workflows The project spanned over 20,000+ video clips and was part of a long-term engagement focused on enhancing machine learning model reliability in real-world environments.

This project involved detailed video annotation for computer vision models used in autonomous vehicle training and smart surveillance systems. I was responsible for accurately identifying and labeling multiple object classes (e.g., pedestrians, vehicles, road signs) across video frames using bounding boxes and polygons. Tasks included: Frame-by-frame tracking of objects across scenes Annotating human actions for behavior analysis Quality assurance reviews to maintain >97% annotation accuracy Strict adherence to complex labeling guidelines and edge-case handling Collaborating with QA and ML engineers to optimize annotation workflows The project spanned over 20,000+ video clips and was part of a long-term engagement focused on enhancing machine learning model reliability in real-world environments.

2020 - 2022

LiDAR Data Annotator Trainer

Remotasks3D SensorSegmentation

At Remotasks, I served as a LiDAR Data Annotator Trainer, specializing in 3D point cloud and object labeling for self-driving car models. I created structured training programs and hands-on sessions to develop proficiency in LiDAR annotation for annotators. My work enabled reliable data for autonomous vehicle model development. • Specialized in 3D point cloud and object annotation for self-driving AI. • Developed and delivered comprehensive LiDAR annotation training materials. • Conducted hands-on instruction focused on annotation guidelines and quality control. • Built a proficient annotation team through continued skill development.

At Remotasks, I served as a LiDAR Data Annotator Trainer, specializing in 3D point cloud and object labeling for self-driving car models. I created structured training programs and hands-on sessions to develop proficiency in LiDAR annotation for annotators. My work enabled reliable data for autonomous vehicle model development. • Specialized in 3D point cloud and object annotation for self-driving AI. • Developed and delivered comprehensive LiDAR annotation training materials. • Conducted hands-on instruction focused on annotation guidelines and quality control. • Built a proficient annotation team through continued skill development.

2020 - 2021

Education

Work History