Maitethia Leakey

I’m a Machine Learning Engineer with a strong economics and quantitative foundation, combining supervised/unsupervised learning with practical model implementation. As a third-year Bachelor of Economics student, I apply econometrics, statistical analysis, and time-series thinking to real behavioral and economic datasets.

I build end-to-end AI workflows: from data cleaning and preprocessing to model evaluation with cross-validation, ROC-AUC, precision-recall, and hyperparameter tuning. My focus spans supervised learning (regression, decision trees, random forests, gradient boosting), unsupervised learning (K-Means, PCA, anomaly detection), and time-series forecasting and sequential pattern recognition.

I also create NLP and LLM-driven systems, including text classification, tokenization, prompt engineering, and structured data extraction through LLM integration. I’ve developed prompt engineering pipelines and AI-assisted automation to support tasks like summarization, content generation, and actionable reporting.

Professionally, I’ve delivered freelance AI-assisted digital support using Python-based data processing and visualization, and I’ve supported accurate financial documentation and reconciliation in an accountant role. I’m passionate about responsible ML—fairness, transparency, and bias-aware development—while shipping useful, data-driven solutions.