Enrico Bovo

I'm a Statistician and Data Analyst with experience in research, public health, and applied data projects. I specialize in statistical modeling, data analysis, and transforming complex datasets into actionable insights and reproducible analytical solutions.

As a Research Fellow on the EU-funded AGE-IT project, I analyzed longitudinal healthcare and environmental datasets with 488k+ observations, developing statistical methods and reproducible workflows for spatial disease mapping and clustering. My work contributed to peer-reviewed publications, conference presentations, and the development of open-source analytical tools for epidemiological research.

I mainly work with R, Python, SQL, and Power BI, building automated workflows, statistical analyses, dashboards, and data-driven reporting solutions. I enjoy combining statistical thinking, problem solving, and clear communication to support research and decision-making processes.

What I can help with:
- Statistical modeling (regression, survival, longitudinal, mixed, and spatial models)
- Data analysis and machine learning in R and Python
- Data cleaning, preprocessing, and feature engineering
- SQL querying and data extraction
- Dashboard development and data visualization with Power BI
- Reproducible workflows, reporting, and analytical research

Highlights:
- Published first/co-author research in Biostatistics (Oxford University Press) and Environmental and Ecological Statistics (Springer)
- Analyzed large-scale healthcare and environmental datasets for public health and ageing research
- Contributed to the development of an open-source R package for spatial disease mapping and clustering
- Presented research at the IEEE CIBCB international conference in Eindhoven
- Delivered guest lectures at the University of Padua on spatial epidemiology and statistical modeling
- Built end-to-end analytical workflows combining data engineering, statistical analysis, and visualization