Professional Overview
Statistics and Programming undergraduate with hands-on experience using Python, SQL, Pandas, scikit-learn and statistical modelling to turn large datasets into analytical findings and decision-support outputs. Experienced in data cleaning and validation, exploratory analysis, classification and regression, model evaluation, and communicating results through dashboards and interactive applications. Built projects across healthcare, environmental, financial and socioeconomic datasets, including imbalanced predictive modelling and analysis of 253,680 public-health records.
Areas of Expertise
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
