Charles A.

Key Skills

Software

AWS SageMaker

Appen

Data Annotation Tech

Top Subject Matter

Financial market prediction (Bitcoin dip forecasting)

Real-time analytics for WiFi-sharing platform

Legal Services & Contract Review

Top Data Types

Text

Document

Image

Top Task Types

Fine-tuning

Data Collection

Text Generation

Transcription

Segmentation

Classification

Object Detection

Question Answering

Text Summarization

Freelancer Overview

Career Pause & Professional Development—Northumbria University (Dissertation: Bitcoin Dip Prediction Using Machine Learn. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Python (pandas, scikit-learn, and TensorFlow. Education includes Master of Science, University of Northumbria (2025) and Bachelor of Science, Madonna University (2019). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Fine-tuning and Data Collection.

Labeling Experience

Career Pause & Professional Development—Northumbria University (Dissertation: Bitcoin Dip Prediction Using Machine Learning)

Fine-tuning

Executed an AI dissertation on predicting short-term Bitcoin market dips using supervised machine learning models. Built and maintained machine learning pipelines covering data ingestion, feature engineering, model training, evaluation, and visualization. Performed rigorous cross-validation and hyperparameter tuning to improve predictive performance and risk assessment. • Model development with Random Forest and XGBoost • Pipeline implementation with pandas and scikit-learn • Training and evaluation with TensorFlow/PyTorch • Visualization and reporting with matplotlib/seaborn

2023 - 2025

Junior Database Administrator—Wicrypt

Data Collection

Developed and optimized SQL and shell-script workflows to extract, aggregate, and report WiFi usage metrics for analytics and operational reporting. Created real-time analytics dashboards to monitor system uptime and user engagement, supporting stakeholder decision-making. Implemented database-level performance improvements by analyzing slow queries and indexes to accelerate data retrieval. • SQL extraction and aggregation for weekly/monthly metrics • Dashboard-oriented real-time analytics support • Query and index optimization reducing execution time • Data consistency across integrated platforms

2020 - 2022

Education

Work History