As a data scientist and analyst, I translate data into valuable and intelligible insights. I aim to improve results, make the right decisions and provide the best outcomes. I have a decade of experience in the tertiary education sector as an educator, researcher and administrator. I am experienced in machine learning, supervised and unsupervised algorithms, statistical analysis and use data visualisation techniques to present the results in an accessible and interpretable way. I use SQL, R, and Python for my data projects.
Executed responsibilities in alignment with procedures in the Department of Architecture, Building and Planning. Managed the administration of results across the faculty including the collection, certification and amendment of results in line with university policy and processes. Program support for academic staff in specified disciplines within the faculty. Managed the set up and administration of student ballots. Managed quota subject selection. Support subject field trip administration including application approvals, funding, risk assessments and liaison with relevant internal and external stakeholders.
Executed responsibilities in alignment with procedures in the Department of Political Science at Melbourne University; identified strategic ways of enhancing stakeholder retention and improving stakeholder engagement; provide feedback and analysis on stakeholder assessment.
Executed responsibilities in alignment with procedures in the Department of Philosophy at Macquarie University; identified strategic ways of enhancing stakeholder retention and improving stakeholder engagement; provide feedback and analysis on stakeholder assessment; developed strategies for multi-modal teaching delivery.
As an assistant grant officer within the Monash University Research Office, my role was to support stakeholders in managing grant opportunities and the grant awards process. This involved but was not limited to grant discovery and interpretation, application support, documentation and compliance, communication with a variety of stakeholders including academics, University Research offices, and funding bodies
Relevant Coursework: Machine Learning, Statistical Data Analysis, Bayesian Learning, Graphical Models, Marketing Analysis, Deep Learning, Human-Aligned Artificial Intelligence
Completed a doctorate in Philosophy. The dissertation explored the development of the concept of equality in the Kantian political tradition.
This project presents a simple prediction analysis using multiple machine-learning tools and techniques. It uses the Wisconsin Breast Cancer Diagnostic prediction dataset. It uses models such as Naive Bayes, Logistic Regression, KNN, Random Forest, SVM and XGBClassifer, and voting techniques. The code is in Python and utilises libraries such as Pandas, numpy, sklearn, and matplotlib. Using a voting classifier ensemble method we were able to succeed in producing a model which was 97% accurate. With a 95% precision rate, 97% recall and 96% f1-score.
View ProjectThis project explores the effects of extreme weather on hospital admissions. It utilises hospital and weather data from the Perth region. The project is split into two main parts. The first part of this project explores hospital data and conducts statistical analysis such as binomial and Poisson distributions to chart the attendance, admission and triage of hospitals in the Perth region on a daily basis. The second part of this project utilises weather data from NOAA to explore whether extreme changes in weather patterns have a correlation with an increase in hospital attendance and admission. Skills developed in this project include: Data cleaning and preparation and advanced statistical data analysis.
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