Data Science Student · Analytics, Machine Learning, NLP & Human-Centred Problem Solving
I am a Master of Data Science student at James Cook University with a strong interest in applied analytics, machine learning, natural language processing, and real-world problem solving. I bring frontline human services experience to every model I build.
Master of Data Science (Professional) at James Cook University, Cairns - building deep expertise in machine learning, NLP, statistical analysis, and applied analytics.
Proficient in Python, R, and SQL. Experienced with end-to-end pipelines - from web scraping and data wrangling to model training, evaluation, and visualisation.
Background in support work, youth services, and community environments - bringing stakeholder awareness, structured reporting, and communication to technical work.
Kenyan-Australian perspective spanning healthcare, international development, and community services - informing a uniquely empathetic approach to data problems.
I am an emerging data scientist who combines rigorous technical training with deep human services experience. My academic work at James Cook University has equipped me with strong foundations in machine learning, NLP, statistical modelling, and data visualisation, while my professional background in homelessness case management, residential youth support, and community care has given me something most data scientists lack: the ability to see the people behind the data.
I am particularly interested in health data, social impact analytics, intelligent systems, and innovation that makes real differences in people's lives. My projects span sentiment analysis, computer vision, IoT systems, and AI-powered advocacy tools, each one grounded in a genuine need I've observed firsthand.
What sets me apart is the ability to combine technical execution with clear communication and thoughtful design. I build models that work, dashboards that tell stories, and presentations that move stakeholders to action. I write code and I write compellingly about what that code means.
A full-stack data science toolkit, from statistical foundations to deployed applications paired with the professional strengths that make technical work meaningful.
Every project starts with a real question. These represent end-to-end data science - from problem framing through deployment.
Full 11-step data science pipeline analysing 1,200+ social media comments. Dual-model scoring with VADER and TextBlob, ensemble classification, LDA topic modelling, temporal trend analysis, and word cloud generation.
Designed an intelligent system that scans government eligibility rules, matches client profiles, and identifies unclaimed benefits for vulnerable populations. Grounded in frontline homelessness case work and real service data.
Deployed a two-device IoT system using computer vision (YOLO + OpenCV) with LoRa mesh telemetry. Live Flask dashboard showing quality percentages, stock levels, and sales inference from edge devices.
Built a MobileNetV2 transfer learning model for agricultural disease detection from leaf images, with multilingual treatment recommendations. Targeted at smallholder farmers in resource-limited settings.
Three progressive notebooks building transformer models from scratch: character-level GPT, document-parsing RAG with cross-attention, and web-scraping GPT with hybrid TF-IDF + BM25 retrieval.
A trajectory from frontline human services to applied data science - each role building on the last.
Open to data science roles, research collaborations, and partnerships - especially where analytics meets real-world human impact.