Professional Overview
Data Scientist with practical experience using Python, SQL and machine learning to analyse large datasets, build predictive models and translate findings into useful business insights. Experienced across the data science lifecycle, from data preparation and feature engineering through model development, evaluation and interactive delivery.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Analysed a retail banking dataset containing over one million transactions
- Developed BG/NBD purchase-frequency and Random Forest revenue and churn models
- Built interactive Streamlit and Plotly dashboards that allowed customer segments
- Participated in peer code reviews using Git/GitHub workflows
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Developed automated operational reporting workflows using Python and SQL
- Analysed system logs and infrastructure performance data across an environment
- Configured, deployed, and managed PC and Mac hardware
Education
Field of Study: Data Science
Field of Study: Information Technology
Areas of Expertise
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
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.
