- Employed Monte Carlo simulations to analyse cost-sensitivity of pass-thresholds.- Designed and implemented a Python-based automated system to streamline the identification of assessment items on cheating websites, enhancing the process of maintaining the integrity of assessment materials.- Conducted a thorough study assessing the robustness of our assessments against the potential challenges posed by Generative AI, yielding actionable insights to reinforce assessment security.- Utilised the Playwright framework to facilitate the automation of assessment solution testing, increasing testing efficiency and reliability.- Built an ETL process to efficiently maintain a database containing volunteer details for future research. This contained controls to ensure compliance with business rules and to prevent duplicate records for occurring.

- Developed and maintained Python and MySQL-based automated data pipelines to consolidate business reporting and enhance dashboard functionality.- Implemented a text-mining process to cleanse and refine comment data, enabling the extraction of pertinent keywords, and conducted sentiment analysis and topic modelling to derive meaningful insights from the comments.- Crafted a regression model aimed at predicting employee turnover by analysing their engagement with e-learning materials.- Performed analysis on employee feedback survey results, providing detailed reports to inform decision-making among senior leadership.- Produced instructional video content designed to help users navigate and comprehend various aspects of learning analytics dashboards effectively.- Facilitated instructional sessions for staff, providing guidance on the utilisation of key learning analytics reports for better data-driven decision-making.

- Developed SQL-based automated data pipelines central to a major financial remediation initiative, including an ETL (Extract, Transform, Load) process for integrating diverse external data sources. - Crafted custom stored procedures to standardise and clean the data in preparation for analysis.- Diagnosed and resolved coding discrepancies, ensuring accuracy and functionality of financial software, while providing comprehensive solutions to client queries.- Collaborated closely with clients to grasp their business needs and ensured these requirements were precisely represented in the programmatic solutions developed.- Meticulously documented code and associated logic to uphold high standards of transparency and accountability for future audits and reviews.- Actively participated in working group meetings, delivering regular status updates to maintain transparent communication with clients regarding project progress.- Leveraged Python to further streamline the reporting process, significantly reducing the dependence on manual spreadsheet updates for routine reporting tasks.

As an Educational Data Scientist, I had the privilege of reporting directly to the Deputy Pro-Vice Chancellor of Education and playing a pivotal role in advancing the university's Learning Analytics initiatives on a large scale. I focused on:- Synthesising and documenting vast amounts of educational data sourced from Oracle and Redshift databases, a process which required close collaboration with various university stakeholders to harness their domain expertise.- Engineering Python and SQL scripts to construct robust ETL workflows, crucial for generating metrics that underpinned machine learning models aimed at bolstering student retention initiatives. These metrics were instrumental during the Victorian COVID-19 lockdowns and were prominently featured in analytical dashboards used by retention services.- Crafting detailed analytical reports for senior academic leadership employing advanced R-based statistical techniques, including regression, factor and cluster analysis, text analysis, and event-sequence analysis. My work included utilising structural topic modelling to dissect open-text responses in surveys, enlightening our understanding of student experiences segmented by demographics.- Developing interactive Shiny R reports that encapsulated predictive models to identify at-risk students, thereby facilitating timely and informed intervention from faculty and support staff.Providing expert statistical consultation to faculty researchers, aiding in data analysis approaches and the composition of results. This was complemented by mentoring graduate and PhD students, offering guidance on statistical methodologies, variable measurement techniques, and the articulation of findings for scholarly publication.- Contributing scholarly articles to top-tier journals in education, with topics encompassing psychometric analysis, predictive modelling, and network analysis, thereby enriching the academic community's knowledge and resources.

- Investigating stakeholder perspectives and expectations regarding the implementation of learning analytics in higher education. This study aimed to uncover the ethical considerations and service expectations that students and staff hold towards learning analytics platforms within university settings.- Collaborating on the EU-funded SHEILA project, a collective effort dedicated to understanding and shaping the landscape of learning analytics adoption across European universities.- Playing a pivotal role in the development and deployment of comprehensive surveys aimed at both students and academic staff. These surveys are meticulously designed to extract valuable insights about the broader acceptance and anticipated impact of learning analytics services.- Analysing the resulting data to contribute meaningful contributions to the project's objectives, with the ultimate goal of informing the ethical and service delivery standards for future learning analytics initiatives in the academic sector.

I undertook qualitative research to investigate the changes in the parent-child relationship following bereavement.