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Peace Uzoukwu

Data Analyst

United Kingdom flagNorwich, United Kingdom
$20.00/hrIntermediateClickworkerCVATAws Sagemaker

Key Skills

Software

ClickworkerClickworker
CVATCVAT
AWS SageMakerAWS SageMaker
LabelboxLabelbox
Label StudioLabel Studio
Micro1
MercorMercor
OneFormaOneForma
RemotasksRemotasks
Scale AIScale AI
SuperviselySupervisely

Top Subject Matter

Legal Services & Contract Review
Regulatory Compliance & Risk Analysis
Legal Research & Document Analysis

Top Data Types

TextText
ImageImage
VideoVideo

Top Task Types

SegmentationSegmentation

Freelancer Overview

Detail-oriented and quality-driven Data Labeling Specialist with hands-on experience working on the Outlier AI platform. Skilled in annotating, reviewing, and validating large datasets to support the development of high-performing machine learning models. Adept at following complex annotation guidelines while maintaining consistency, accuracy, and efficiency across diverse data types. Proven ability to work independently in fast-paced, remote environments, meeting tight deadlines without compromising quality. Experienced in handling text-based labeling tasks, including classification, ranking, and content evaluation, with a strong understanding of how labeled data impacts AI model performance. Key strengths include attention to detail, analytical thinking, and adaptability when working with evolving project requirements. Comfortable collaborating with distributed teams, incorporating feedback, and continuously improving annotation quality to meet project standards. Committed to maintaining data integrity and confidentiality while contributing to scalable AI solutions.

IntermediateEnglishFrench

Labeling Experience

AI Training Data Annotation for Audio Transcription & Classification

AudioTranscription
Contributed to audio data annotation projects through Outlier AI, supporting the development of speech recognition and audio-based AI systems. Tasks included transcribing spoken content with high accuracy, classifying audio segments, and analyzing tone, intent, and sentiment. Worked with diverse audio samples, including varying accents, speech patterns, and background noise conditions. Applied detailed guidelines to ensure precise transcription, correct labeling of audio categories, and consistent sentiment evaluation across datasets. Demonstrated strong listening skills and attention to detail when handling unclear or noisy recordings, using context to resolve ambiguities while maintaining annotation quality. Met strict accuracy benchmarks and turnaround times in a fast-paced, remote work environment. Incorporated feedback from quality reviews to continuously improve performance and ensure alignment with project standards. This work contributed to the training of AI models used in voice assistants, automated transcription services, and audio content analysis.

Contributed to audio data annotation projects through Outlier AI, supporting the development of speech recognition and audio-based AI systems. Tasks included transcribing spoken content with high accuracy, classifying audio segments, and analyzing tone, intent, and sentiment. Worked with diverse audio samples, including varying accents, speech patterns, and background noise conditions. Applied detailed guidelines to ensure precise transcription, correct labeling of audio categories, and consistent sentiment evaluation across datasets. Demonstrated strong listening skills and attention to detail when handling unclear or noisy recordings, using context to resolve ambiguities while maintaining annotation quality. Met strict accuracy benchmarks and turnaround times in a fast-paced, remote work environment. Incorporated feedback from quality reviews to continuously improve performance and ensure alignment with project standards. This work contributed to the training of AI models used in voice assistants, automated transcription services, and audio content analysis.

2024 - 2026

AI Training Data Annotation for Video Content Analysis & Classification

VideoSegmentation
Worked on video annotation projects via Outlier AI, supporting the development of AI models for video understanding and content moderation. Analyzed video clips to classify content, tag key events, and segment sequences based on actions, behaviors, or contextual changes over time. Applied detailed guidelines to ensure accurate labeling across frames, maintaining consistency when identifying objects, actions, and transitions. Demonstrated strong attention to temporal patterns, ensuring annotations reflected not just what appears in a single frame but how it evolves throughout the video. Handled complex and ambiguous scenarios, including fast-moving scenes and overlapping actions, using critical judgment to align with project standards. Maintained high accuracy while working within tight deadlines and large-scale datasets. Collaborated with distributed teams and incorporated feedback to continuously improve annotation quality, contributing to robust training datasets for AI systems used in surveillance, media analysis, and automated content moderation.

Worked on video annotation projects via Outlier AI, supporting the development of AI models for video understanding and content moderation. Analyzed video clips to classify content, tag key events, and segment sequences based on actions, behaviors, or contextual changes over time. Applied detailed guidelines to ensure accurate labeling across frames, maintaining consistency when identifying objects, actions, and transitions. Demonstrated strong attention to temporal patterns, ensuring annotations reflected not just what appears in a single frame but how it evolves throughout the video. Handled complex and ambiguous scenarios, including fast-moving scenes and overlapping actions, using critical judgment to align with project standards. Maintained high accuracy while working within tight deadlines and large-scale datasets. Collaborated with distributed teams and incorporated feedback to continuously improve annotation quality, contributing to robust training datasets for AI systems used in surveillance, media analysis, and automated content moderation.

2024 - 2026

AI Training Data Annotation for Content Classification & Ranking

TextClassification
Contributed to AI training initiatives on the Outlier AI by performing high-quality text annotation for content classification, ranking, and sentiment analysis tasks. Evaluated and labeled diverse text data, including user-generated content and AI-generated responses, to improve the performance and reliability of natural language processing models. Applied detailed annotation guidelines to categorize content accurately, assess sentiment, and rank outputs based on relevance, quality, and safety. Demonstrated strong judgment in identifying nuanced language patterns, including tone, intent, and potentially sensitive or harmful content. Maintained consistency and precision across large datasets while meeting strict quality standards and deadlines. Regularly handled edge cases and ambiguous inputs, ensuring decisions aligned with project requirements. Incorporated feedback from quality reviews to continuously refine annotation accuracy. This work directly supported the development of more effective and safe AI systems used in content moderation and language understanding applications.

Contributed to AI training initiatives on the Outlier AI by performing high-quality text annotation for content classification, ranking, and sentiment analysis tasks. Evaluated and labeled diverse text data, including user-generated content and AI-generated responses, to improve the performance and reliability of natural language processing models. Applied detailed annotation guidelines to categorize content accurately, assess sentiment, and rank outputs based on relevance, quality, and safety. Demonstrated strong judgment in identifying nuanced language patterns, including tone, intent, and potentially sensitive or harmful content. Maintained consistency and precision across large datasets while meeting strict quality standards and deadlines. Regularly handled edge cases and ambiguous inputs, ensuring decisions aligned with project requirements. Incorporated feedback from quality reviews to continuously refine annotation accuracy. This work directly supported the development of more effective and safe AI systems used in content moderation and language understanding applications.

2024 - 2026

Computer Vision Data Annotation for Object Detection Models

ImageBounding Box
Worked on large-scale image annotation projects through Outlier AI, supporting the development of computer vision models. Responsibilities included drawing precise bounding boxes around objects of interest, ensuring accurate object localization and consistent labeling across diverse image datasets. Followed detailed annotation guidelines to identify and label multiple object classes, even in complex or cluttered scenes. Maintained high accuracy and consistency while meeting strict quality benchmarks and turnaround times. Regularly reviewed edge cases and ambiguous images, applying critical thinking to ensure reliable annotations aligned with project standards. Collaborated within a distributed team environment, incorporating feedback from quality reviewers to continuously improve performance. Contributed to producing high-quality labeled datasets used for training and optimizing machine learning models in real-world applications.

Worked on large-scale image annotation projects through Outlier AI, supporting the development of computer vision models. Responsibilities included drawing precise bounding boxes around objects of interest, ensuring accurate object localization and consistent labeling across diverse image datasets. Followed detailed annotation guidelines to identify and label multiple object classes, even in complex or cluttered scenes. Maintained high accuracy and consistency while meeting strict quality benchmarks and turnaround times. Regularly reviewed edge cases and ambiguous images, applying critical thinking to ensure reliable annotations aligned with project standards. Collaborated within a distributed team environment, incorporating feedback from quality reviewers to continuously improve performance. Contributed to producing high-quality labeled datasets used for training and optimizing machine learning models in real-world applications.

2024 - 2026

Data Analyst

Segmentation
As a Data Analyst at Chellarams PLC, I drove data-driven strategy through segmentation, dashboard deployment, and process automation for manufacturing and consulting clients. I implemented cloud-based analytics infrastructure and led workshops that encouraged a data-driven culture. Proficiency in Tableau, Power BI, SQL, and Excel was essential for efficient data preparation and stakeholder engagement. • Conducted customer segmentation and retention analytics • Integrated AWS cloud services for scalable data storage and analytics • Built dashboards to reduce manual reporting and improve engagement • Automated workflows and delivered client training sessions

As a Data Analyst at Chellarams PLC, I drove data-driven strategy through segmentation, dashboard deployment, and process automation for manufacturing and consulting clients. I implemented cloud-based analytics infrastructure and led workshops that encouraged a data-driven culture. Proficiency in Tableau, Power BI, SQL, and Excel was essential for efficient data preparation and stakeholder engagement. • Conducted customer segmentation and retention analytics • Integrated AWS cloud services for scalable data storage and analytics • Built dashboards to reduce manual reporting and improve engagement • Automated workflows and delivered client training sessions

2020 - 2022

Education

U

University of Derby

Master of Science, Management

Master of Science
2023 - 2024
U

University of Nigeria, Nsukka

Bachelor of Arts, Foreign Language

Bachelor of Arts
2014 - 2018

Work History

T

Teleperformance

Review Officer

Derby
2024 - Present
T

Teleperformance

Customer Success Advisor

Derby
2024 - 2024