Transcribed Gulf Arabic and MSA audio in full verbatim, accurately labeling speakers, timestamps, and overlapping dialogue
LinkedIn Learning | Course by Wuraola Oyewusi
Core Achievement: Completed a comprehensive, project-based training program focused on applied data annotation for computer vision and NLP. Gained practical, hands-on experience across the entire annotation lifecycle, from data setup to quality assurance, using a wide range of industry-standard platforms and tools.
Key Accomplishments & Skills Gained:
Multi-Platform Proficiency: Successfully executed end-to-end annotation projects on major cloud platforms (AWS SageMaker, Azure ML) and open-source tools (CVAT, Roboflow), demonstrating the ability to quickly adapt to different UIs and workflows.
Computer Vision Annotation: Applied a range of techniques to a 12-image "Cars on the Street" dataset, including object detection (labeling 80+ instances of cars with bounding boxes), object classification (labeling 100+ images of boots or sneakers), and instance segmentation (creating precise polygon masks). Also completed a 45-image single-label classification project.
NLP & Audio Annotation: Performed core NLP annotation tasks on a sample text corpus, including Named Entity Recognition (NER) (labeling 15+ entities like ORG and PERSON) and sentiment analysis. Also practiced audio transcription and diarization on a multi-language audio file.
Model-Assisted Labeling: Increased annotation efficiency by leveraging AI-powered tools, using a YOLOv7 model in CVAT and Label Assist in Roboflow to generate initial labels for review and correction. Also practiced with the advanced Segment Anything
Model (SAM) for high-quality, semi-automated polygon masking. Formats: Successfully exported final datasets in multiple industry-standard formats, including COCO (JSON), Pascal VOC (XML), and YOLO (TXT).
Skills: Cloud Annotation Platforms (AWS SageMaker, Azure ML) · Data Annotation Tools (CVAT, Roboflow, UDT) · Computer Vision (Object Detection, Instance Segmentation) · NLP (NER, Sentiment Analysis) · Model-Assisted Labeling · Annotation Formats (COCO, YOLO).
Portfolio: [link]
Created high-quality, diverse training data across multiple annotation verticals to power the development of advanced computer vision, OCR, and data-extraction models.
Polygon Image Segmentation (Cropping Spaces): Applied complex polygon segmentation techniques to 46 document images, isolating pages from cluttered backgrounds and correcting for image skew and rotation to create clean, machine-readable inputs. 4 mins/image.
Bounding-box annotation (Box 20 Words): Annotated around 1,000 words across 50 tasks [English, Arabic, Hebrew, Hindi, CJK (Chinese, Japanese, or Korean)]; 7–8 min/task, 2–3 words/min. Produced tight, rotated boxes for angled and handwritten text.
Complex document labeling (Document Derby): Annotated 5 diverse, multilingual documents (English/Japanese), dedicating an average of 48 minutes per document to apply a complex schema of up to 50+ detailed labels to layouts like invoices and medical forms.
Text Legibility Classification (Can You Really Read Me?): Executed high-speed OCR data validation across Arabic, English, CJK (Chinese, Japanese, or Korean), and Indian scripts — classified 268 text samples at an average speed of 8 tasks per minute. Applied precise labels based on clarity (blurry), completeness (occluded), and stylization (unknown script).
Video Content Analysis & Timestamping (Commercial Labeling v3): Performed detailed analysis of 32 video segments at an efficient pace of 1.5 minutes per task. Applied precise, frame-level intro/outro timestamps and performed multi-level content classification (e.g.,
Commercial, TV Promo). Required nuanced decision-making based on a complex rubric, including hierarchical brand/product identification and context-based rules for streaming service promotions.
Image Quality Analyst (Blurry or Not): Validated the quality of 96 multilingual documents (Arabic, English, Hindi, Hebrew, Japanese), executing a binary classification task at an efficient pace of 4.2 tasks per minute to reject blurred or corrupted images and ensure a high-quality input for machine learning models.
Annotation Quality Assurance & Review (Getting Your Docs in a Row): Served as a key quality reviewer, auditing 30 pre-annotated documents at an efficient pace of 2 minutes per task. Applied expert knowledge of a complex annotation schema (20+ labels, including Tables, KV Areas, and Figures) to make nuanced "Approve/Reject" judgments on multilingual submissions, achieving a 100% task acceptance rate for quality assurance work.
Process-Driven Quality Assurance: Developed and implemented comprehensive checklists based on detailed project instructions to ensure methodical and consistent application of annotation rules, resulting in a 96.6% overall task acceptance rate across 527 submissions.
Skills: Multimodal Data Annotation (Image, Text, Video) · Multilingual Labeling [English, Arabic, Hebrew, Hindi, Chinese, Japanese, Korean (CJK)] · Quality Assurance (QA) & Review · Bounding-Box · Polygon Segmentation · Complex Document Labeling · Video Timestamping · Attention to Detail · Image Quality Assessment
Project Goal: To master the professional standards of audio transcription and QA by applying industry-leading guidelines to a variety of Arabic audio samples.
Executed clean verbatim transcription of a 3-minute, Saudi Arabic interview, meticulously adhering to GoTranscript's style guide to achieve a self-assessed 98% accuracy score.
Performed a critical QA role by auditing and correcting 10 AI-generated (HappyScribe) transcripts in both MSA and Lebanese Arabic, reformatting them to meet the rigorous GoTranscript quality standards for STT model training.
Skills: Audio Transcription (Arabic) · Transcription QA · Dialect Comprehension (Saudi, MSA, Lebanese) · Guideline Adherence · Attention to Detail · Timestamping · Self-Assessment & Quality Control
3-Min Saudi Arabic Transcript: [link]
10 Arabic QA Transcript Samples: [link]
Core Achievement: Built an e-commerce business from the ground up on the Amazon KDP platform, managing the complete product lifecycle from market research and design to publishing and performance analysis.
Key Accomplishments & Skills:
Market & Keyword Research: Utilized BookBolt to conduct in-depth market analysis, identifying high-demand, low-competition niches for puzzle books. Performed extensive keyword research to target specific customer segments, including adults, seniors, and kids.
AI Model Analysis (R&D): Conducted a comparative analysis of multiple Large Language Models (LLMs) to optimize the word list generation process. Performed a quantitative evaluation of LLM performance based on data accuracy, relevancy, and efficiency to select the optimal tool.
Product Design & Development: Conceptualized and developed multiple word search puzzle books. Managed the entire design process, creating professional, print-ready covers and interior layouts using specialized software (BookBolt) to meet Amazon's strict technical specifications.
E-commerce Merchandising & SEO: Wrote compelling, SEO-optimized titles, subtitles, and descriptions to maximize visibility and ranking within Amazon's A10 search algorithm. Differentiated products by creating various formats, including hardcover, paperback, and large print.
Performance Tracking & Analytics: Developed and maintained a comprehensive analytics spreadsheet to track key performance indicators (KPIs) and derive actionable insights to guide future product strategy.
Skills: Market Research (BookBolt) · Keyword Analysis · AI Tool Evaluation (LLMs) · Product Design · E-commerce SEO · Data Tracking & Analytics · Project Management
Portfolio: [link]
Engineered 20+ advanced AI prompts to optimize LLM outputs across diverse domains, including SEO content, high-converting book covers and descriptions, fiction/nonfiction book summaries, customized professional CVs, and large word search lists (500 words each)
Developed a suite of prompts for high-performance content generation, focusing on SEO optimization for first-page article ranking and high-conversion copywriting for blog excerpts and e-commerce platforms (Amazon KDP).
Engineered sophisticated prompts for complex data synthesis, successfully summarizing full-length fiction/non-fiction books and technical YouTube videos into concise, structured formats.
Applied prompt engineering principles to career development, creating a systematic workflow to generate, iterate on, and quality-check world-class CVs, LinkedIn profiles, and other professional branding materials.
Leveraged text-to-image prompting techniques to conceptualize and generate high-converting cover designs for Amazon KDP puzzle books, testing various artistic styles and compositions to align with target market aesthetics.
Skills: Prompt Engineering · LLM Evaluation & Optimization · Content Generation · Data Synthesis · Text-to-Image Prompting · Iterative Testing · Workflow Automation
Portfolio: [link]
Core Achievement: Engineered a highly efficient, AI-powered content pipeline for YouTube Shorts, successfully building and managing a channel designed for affiliate marketing.
Key Accomplishments & Skills:
Business & Content Strategy: Developed a channel concept and content strategy focused on AI-generated humor to attract a specific target audience. Placed strategic affiliate links in pinned comments to convert channel traffic into revenue.
AI-Powered Content Pipeline: Engineered a streamlined workflow for mass content production. Utilized generative AI (ChatGPT) for script ideation and a custom-built HTML tool (JokeFilter Pro) to rapidly moderate and filter joke outputs for quality and brand safety.
Automated Video Production: Leveraged an AI video generation tool (Pictory.ai) to convert finalized scripts into engaging short-form videos, managing the full production cycle from text to final export.
Channel Growth & Optimization: Managed all platform operations, including video uploads, scheduling, and data-driven optimization of titles and thumbnails to maximize visibility and audience engagement within the YouTube Shorts algorithm.
Skills: Affiliate Marketing · Content Strategy · Generative AI Tools (ChatGPT) · Automated Video Production (Pictory.ai) · Workflow Automation · YouTube SEO
Portfolio: [link]
Core Achievement: Built and grew two affiliate blog sites from scratch, engineering a comprehensive SEO project management system to move from initial concept to first-page Google rankings.
Key Accomplishments & Skills:
Data-Driven Niche Validation: Developed a sophisticated framework in Sheets to forecast niche profitability, systematically evaluating opportunities against 15+ criteria (KD, Search Volume, EPMP, YMYL risk). Utilized this system to analyze macro-niches and strategically select high-potential verticals.
SEO Performance Analysis & Optimization: Systematically tracked SERP rankings for all target keywords on a dedicated progress sheet. Analyzed this performance data to identify underperforming content, diagnose on-page issues, and execute iterative updates that successfully improved organic rankings.
Full-Funnel Keyword Strategy: Executed an end-to-end keyword research process, identifying thousands of potential keywords and filtering them down to low-competition, high-intent topics with a clear path to achieving topical authority.
Content Creation & SEO Copywriting: Wrote, edited, and published dozens of long-form articles, securing multiple first-page rankings by integrating best-practice SEO into engaging, user-focused content.
A/B Testing & CRO: Designed and ran A/B tests on on-page elements, such as CTA text and banner placement, analyzing performance data to improve click-through rates and affiliate conversions.
Skills: SEO Strategy · Keyword Research (Semrush) · Content Strategy & Creation · SEO Copywriting · SERP Tracking · Data Analysis (Google Sheets, GSC) · A/B Testing & CRO · Affiliate Marketing · Project Management · WordPress
First Affiliate Blog Site (WayBack Machine): [link]
Second Affiliate Blog Site (WayBack Machine): [link]
View Niche Research & Brand Assets: [link]
Core Achievement: Successfully launched a Print-on-Demand (POD) e-commerce business, managing the complete product lifecycle from data-driven market research to final product listing and SEO.
Market & Niche Analysis: Utilized Merch Informer to conduct keyword research and competitive analysis, identifying a profitable niche for original t-shirt designs.
Product Design & Development: Created a portfolio of original graphic designs using Canva and PhotoPea, tailored to the aesthetic and interests of the target market niche.
E-commerce SEO & Merchandising: Wrote compelling, SEO-optimized titles and product descriptions to maximize organic visibility and drive traffic within the Amazon marketplace.
Skills: Market Research (Merch Informer) · E-commerce SEO · SEO Copywriting · Graphic Design (Canva, PhotoPea) · Print-on-Demand (POD)
Portfolio: [link]
An AI Training Data Specialist with a background in Electrical Engineering, I have a proven track record of creating high-quality, diverse, and multilingual datasets that power AI. My expertise spans the full data lifecycle, from collection and multi-platform annotation to meticulous Quality Assurance.
My unique value lies in four key areas:
Analytical & Mathematical Rigor: Leveraging a Bachelor's in Electrical Engineering from the globally-ranked KFUPM and a university Calculus Excellence Award, I apply strong analytical and logical reasoning to ensure the highest levels of data integrity, accuracy, and consistency in every task.
️ Native Arabic Linguist: Native fluency in the Saudi Gulf dialect, strong comprehension of major Arabic regional dialects (Egyptian, Levantine, Hijazi, Najdi, Yamani), and a university-level distinction in Modern Standard Arabic (MSA). I provide the nuanced cultural and linguistic expertise required for world-class Arabic language models.
Multimodal Data Annotation: Hands-on experience across data types, including Text, Image, Audio, Video, and 3D LiDAR point clouds. Familiar with platforms like AWS SageMaker, Azure ML, CVAT, Supervisely, UDT, and Roboflow, applying techniques from bounding boxes to complex polygon segmentation.
Data Quality Assurance: Achieved a 96.6% overall task acceptance rate across 527 submissions on Hive Micro and a 100% success rate in a dedicated QA review role. I excel at auditing data against complex rubrics to ensure it is accurate and consistent.
I am currently seeking remote, project-based opportunities (part-time or contract, at least 20 hours/week) in AI Training Data, Math & Logic AI Training/Evaluation, and Arabic linguistic annotation. I operate from a fully-equipped home office, ensuring reliable and secure delivery on all projects.
Institutional Ranking: #1 in the Arab Region (QS 2026) #67 worldwide (QS 2026), a ranking higher than all but 19 US universities.
Admission Selectivity: Secured admission as part of the top 5% of the university's incoming student body.
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