Lucas Bianchi

I am a Statistician and Data Scientist with a PhD in Epidemiology and around 9 years of experience working with data analysis, statistical modeling, dashboards, and applied research.

My work focuses on transforming complex data into clear, actionable insights. I have experience with statistical analysis, predictive modeling, data visualization, automated reports, and interactive dashboards, especially using R, Shiny, Python, SQL, BigQuery, and cloud-based tools.

I have worked on projects in public health, epidemiology, market research, survey analysis, monitoring systems, and decision-support platforms. I can help with everything from cleaning and structuring data to developing complete analytical workflows, building dashboards, writing reports, and interpreting results.

My main skills include

Statistical analysis and modeling

Survey design and questionnaire analysis

Data cleaning, ETL, and automation

R, Shiny, Python, SQL, and BigQuery

Interactive dashboards and data visualization

Epidemiology and public health research

Academic and technical reports

Predictive models and monitoring indicators

I am detail-oriented, reliable, and used to working with both technical and non-technical stakeholders. My goal is always to deliver clear, well-documented, and useful results that help clients make better decisions based on data.

I am a Statistician and Data Scientist with a PhD in Epidemiology and around 9 years of professional experience in data analysis, statistical modeling, epidemiological research, dashboards, and data-driven decision support.

Throughout my career, I have worked on projects involving public health, epidemiology, global health monitoring, market research, survey analysis, and business intelligence. My experience includes designing analytical workflows, cleaning and transforming complex datasets, developing statistical and predictive models, creating automated reports, and building interactive dashboards for technical and non-technical audiences.

I have strong experience with R, especially for data manipulation, modeling, reporting, and Shiny dashboard development. I also work with Python, SQL, BigQuery, Docker, Git/GitHub, and cloud-based environments such as Google Cloud Platform. I have developed interactive applications, automated data pipelines, and monitoring tools that help organizations transform raw data into clear insights and practical decisions.

My background also includes survey design, questionnaire analysis, epidemiological indicators, data visualization, ETL processes, and academic/technical reporting. I am used to working with multidisciplinary teams, translating complex analytical results into accessible explanations, and delivering reliable, well-documented solutions.

Overall, my professional experience combines strong statistical expertise, applied data science, software development, and public health knowledge, allowing me to support projects from data preparation and analysis to final reporting, dashboards, and strategic recommendations.

I have a strong academic background in Statistics, Applied Statistics, Biometry, Epidemiology, and Public Health.

I hold a Bachelor’s degree in Statistics, a Master’s degree in Applied Statistics and Biometry, and a PhD in Epidemiology. This academic path gave me a solid foundation in quantitative methods, statistical modeling, study design, epidemiological research, data analysis, and the interpretation of complex datasets.

My education combines rigorous statistical training with applied research experience, especially in health, population studies, public health indicators, and evidence-based decision-making. This background allows me to approach projects with both methodological rigor and practical understanding of real-world data problems.

In addition to my formal education, I have continuously developed technical skills in R, Python, SQL, dashboard development, data visualization, cloud tools, and automated reporting, combining academic research experience with practical data science and software development skills.