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J

Jecinta Mulongo

Data Labeling for Distracted Driver Detection (AI Institute Boot-camp)

KENYA flag
Nairobi, Kenya
$30.00/hrExpertOtherClickworkerCrowdsource

Key Skills

Software

Other
ClickworkerClickworker
CrowdSourceCrowdSource
Img Lab
iMeritiMerit
Micro1

Top Subject Matter

Distracted driver detection using image classification
Document analysis and automation using NLP
Computer vision for security and transportation analytics

Top Data Types

ImageImage
TextText
DocumentDocument

Top Task Types

Classification
Entity Ner Classification
Object Detection

Freelancer Overview

Data Labeling for Distracted Driver Detection (AI Institute Boot-camp). Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include TensorFlow, spaCy, and OpenCV. Education includes Certificate, AI Institute (2019) and Master of Science, African Institute for Mathematical Sciences (2019). AI-training focus includes data types such as Image, Text, and Document and labeling workflows including Classification, Entity (NER) Classification, and Object Detection.

ExpertSwahiliEnglish

Labeling Experience

Text Data Labeling/NLP Entity Annotation (Scigenix, LLM Project)

TextEntity Ner Classification
As Data Scientist at Scigenix (Pty) Ltd, I developed NLP solutions using Large Language Models to automate document analysis. I prepared and labeled text data to extract entities, classifications, and actionable insights for automation and review reduction. The labeling involved NER tagging and preparation of structured datasets for model fine-tuning. • Labeled and annotated textual entities using Python-based NLP tools. • Conducted dataset preparation for large language model fine-tuning. • Used internal scripts and spaCy for annotation and verification tasks. • Ensured quality and scalability for enterprise document NLP pipelines.

As Data Scientist at Scigenix (Pty) Ltd, I developed NLP solutions using Large Language Models to automate document analysis. I prepared and labeled text data to extract entities, classifications, and actionable insights for automation and review reduction. The labeling involved NER tagging and preparation of structured datasets for model fine-tuning. • Labeled and annotated textual entities using Python-based NLP tools. • Conducted dataset preparation for large language model fine-tuning. • Used internal scripts and spaCy for annotation and verification tasks. • Ensured quality and scalability for enterprise document NLP pipelines.

2024 - 2025

Image Annotation for Object Detection (8Teq Kenya)

ImageObject Detection
At 8Teq Kenya, I led the creation and fine-tuning of image classification models using CNNs and YOLO for automated number plate recognition and video analytics. This required extensive image labeling, drawing bounding boxes, and annotating object classes relevant to security and transportation. My work ensured high-precision datasets for real-time deployment scenarios. • Delegated and performed manual labeling of vehicle attributes in images. • Designed and reviewed annotation guidelines to standardize dataset quality. • Utilized Python-based tools and OpenCV for bounding box labeling. • Focused on object detection for automated monitoring systems.

At 8Teq Kenya, I led the creation and fine-tuning of image classification models using CNNs and YOLO for automated number plate recognition and video analytics. This required extensive image labeling, drawing bounding boxes, and annotating object classes relevant to security and transportation. My work ensured high-precision datasets for real-time deployment scenarios. • Delegated and performed manual labeling of vehicle attributes in images. • Designed and reviewed annotation guidelines to standardize dataset quality. • Utilized Python-based tools and OpenCV for bounding box labeling. • Focused on object detection for automated monitoring systems.

2020 - 2022

Structured Data Collection Supervision (KNBS Census)

OtherDocumentClassification
As Census Coordinator at KNBS in 2019, I supervised and coordinated structured data collection. My responsibilities included ensuring enumerators captured and recorded data accurately and according to strict standards. Quality control processes involved reviewing and verifying labeled responses across large document batches. • Trained staff on structured document data labeling. • Enforced accuracy standards in document annotation operations. • Led review cycles for data quality verification. • Managed reporting for structured data annotation projects.

As Census Coordinator at KNBS in 2019, I supervised and coordinated structured data collection. My responsibilities included ensuring enumerators captured and recorded data accurately and according to strict standards. Quality control processes involved reviewing and verifying labeled responses across large document batches. • Trained staff on structured document data labeling. • Enforced accuracy standards in document annotation operations. • Led review cycles for data quality verification. • Managed reporting for structured data annotation projects.

2019 - 2019

Data Labeling for Distracted Driver Detection (AI Institute Boot-camp)

ImageClassification
During the AI Institute Boot-camp, I implemented a mini-project for distracted driver detection using a Convolutional Neural Network. This process required collecting, cleaning, labeling, and annotating images representing different types of driver distractions. I was responsible for preparing the dataset, assigning accurate image labels, and ensuring annotation consistency. • Curated and labeled images for each distraction category. • Utilized Python-based annotation tools and TensorFlow/Keras libraries. • Carried out image classification with supervised learning models. • Ensured high labeling accuracy to improve model performance.

During the AI Institute Boot-camp, I implemented a mini-project for distracted driver detection using a Convolutional Neural Network. This process required collecting, cleaning, labeling, and annotating images representing different types of driver distractions. I was responsible for preparing the dataset, assigning accurate image labels, and ensuring annotation consistency. • Curated and labeled images for each distraction category. • Utilized Python-based annotation tools and TensorFlow/Keras libraries. • Carried out image classification with supervised learning models. • Ensured high labeling accuracy to improve model performance.

2019 - 2019

Education

A

AI Institute

Certificate, Artificial Intelligence

Certificate
2019 - 2019
A

African Institute for Mathematical Sciences

Master of Science, Industrial Mathematics

Master of Science
2017 - 2019

Work History

S

Scigenix

Senior Data Scientist

Nairobi
2025 - Present
S

Scigenix

Data Scientist

Nairobi
2024 - 2025