Serene C.

Key Skills

Software

Data Annotation Tech

Google Cloud Vertex AI

Mercor

Top Subject Matter

AI output evaluation for social media and editorial content

Text content research and AI draft evaluation for esports/gaming writing

Text research and quality control for compliance-sensitive content

Top Data Types

Audio

Computer Code Programming

Document

Image

Text

Video

Top Task Types

Action Recognition

Audio Recording

Classification

Computer Programming/Coding

Evaluation/Rating

Object Detection

Relationship

Text Generation

Text Summarization

Transcription

Translation/Localization

Freelancer Overview

AI-assisted evaluation work within Social Media Marketing operations at Ajegunle Business School. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Claude, ChatGPT, and Canva AI. Education includes Bachelor of Business Administration, Nexford University (2024) and Associate of Applied Science in Business Administration, Nexford University (2022). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI-assisted evaluation work within Social Media Marketing operations at Ajegunle Business School

Text

Managed AI-assisted content ideation and drafting operations while applying structured evaluation checks to ensure output quality. Evaluated AI-generated ideas and drafts for factual accuracy, instruction adherence, tone alignment, formatting quality, and overall coherence prior to publication. Coordinated asynchronous review workflows with distributed stakeholders to maintain editorial and quality standards across campaigns. • Assessed AI outputs for hallucination risk and factual consistency using multi-model tools. • Checked for instruction-following and structural quality (clarity, formatting, coherence). • Maintained operational documentation and KPI reporting for performance tracking. • Used Claude, ChatGPT, and Canva AI to accelerate workflow while preserving quality controls.

2025 - Present

NLP Data Labeling & Text Annotation Specialist

TextEntity (NER) Classification

Worked on natural language processing datasets used for training and improving AI language models and conversational systems. Tasks included labeling text data for sentiment, categorizing user intent, identifying named entities, and ranking model-generated responses based on relevance and quality. Processed diverse datasets including customer support conversations, social media text, and chatbot interactions. Ensured consistency in labeling by strictly following annotation guidelines and resolving ambiguous cases through contextual analysis. Contributed to improving dataset quality through careful review of edge cases, maintaining high accuracy in labeling standards, and supporting model fine-tuning efforts for better response relevance and understanding.

2024 - Present

Video Data Annotation Specialist (AI Training)

VideoObject Detection

Worked on video annotation projects for AI model training focused on object detection, motion tracking, and activity recognition. Tasks included frame-by-frame labeling of moving objects, drawing and adjusting bounding boxes across sequences, and tagging actions or events within video clips. Handled diverse video datasets including street scenes, indoor environments, and user-generated content. Ensured temporal consistency across frames to maintain high-quality tracking labels for machine learning models. Followed strict annotation guidelines and quality control processes, including review cycles and correction of labeling inconsistencies. Maintained accuracy while working with high-volume video datasets under time constraints.

2024 - 2026

AI Data Labeling & Annotation Specialist

TextClassification

Worked on large-scale data labeling projects supporting machine learning model development across multiple domains including e-commerce, social media content moderation, and general object detection tasks. Responsibilities included image classification, bounding box annotation, multi-label tagging, and sentiment labeling of text data. Ensured accurate labeling of diverse datasets by following detailed annotation guidelines and maintaining consistency across large batches of data. The project involved processing thousands of data samples weekly, working with both structured and unstructured datasets. Quality was maintained through strict adherence to annotation guidelines, periodic review cycles, and cross-check validation to minimize labeling errors and improve dataset reliability. All outputs were reviewed against predefined quality benchmarks, including accuracy thresholds and consistency checks, ensuring high-quality training data for downstream AI model training.

2024 - 2025

Content Writer with research-driven accuracy controls at Sterling Bank

Text

Created compliance-sensitive financial and business content requiring high factual accuracy and editorial precision. Performed research across financial and regulatory topics while maintaining structured research archives and editorial records. Supported organized publishing workflows that included documentation, review cycles, and scheduled content releases. • Applied factual accuracy requirements consistent with high-stakes editorial standards. • Maintained structured research archives and editorial records for traceability. • Followed documentation and review-cycle processes within a publishing workflow. • Scheduled and coordinated content within organized editorial operations.

2022 - 2023

Education

Work History