I'm a Biology graduate currently transitioning into data engineering.
During my second year at university, I studied Ecological Data Analysis, which introduced me to working with biological datasets and using R for statistical analysis. I found myself particularly interested in the programming and data analysis side of the course, so in my third year I chose Advanced Data Analysis as one of my optional modules.
Through these modules, I developed experience in data manipulation, statistical modelling, simulation and visualisation. They helped me realise that working with data was something I wanted to pursue beyond my biology degree.
I'm now working towards a career in data engineering, building on my existing R experience while developing my knowledge of Python, SQL, databases and data pipelines.
- Programming: R
- Data work: importing and transforming datasets, data analysis and visualisation
- Modelling: statistical regression, generalised linear models and numerical simulation
- R libraries:
dplyr,tidyr,ggplot2,deSolve, and many more - Tools: RStudio and GitHub
Built an SIR model in R to investigate how different levels of vaccination coverage affect the progression and severity of simulated infectious disease outbreaks. The project includes scenario comparisons, summary statistics and visualisations.
Analysed butterfly abundance and population growth across four monitoring sites in Borneo using R. This project involved working with CSV datasets, statistical modelling, linear regression and data visualisation.
- SQL: querying, joining and aggregating data
- Python: programming and data processing with pandas
- PostgreSQL: relational database fundamentals
- ETL pipelines: extracting, transforming and loading data reliably
My next portfolio goal is to build an end-to-end Python and SQL data pipeline, applying these skills to a real dataset.
I'm interested in junior data engineering and other entry-level data roles where I can continue developing my technical skills and contribute to practical data projects.