BL
About
I am a former researcher transitioning to a data scientist. I have experience in statistical analysis, including descriptive statistics, hypothesis testing, and linear regression, as well as data analysis and visualization using Python and R. I have competence in libraries such as pandas, numpy, matplotlib, seaborn, scikit-learn, tidyverse, dplyr, ggplot2.
Work Experience
Freie Universität BerlinOn-site
2019 - 2023
Research Assistant
- Led long-term research projects, overseeing planning, execution, and achievement of project objectives within specified timelines.
- Analyzed high-dimensional data (over 65,000 data points) using Python and R.
- Presented research findings in multiple formats to audiences of up to 50 people, earning one award for best presentation.
- Mentored junior team members, offering technical guidance to ensure appropriate experimental design and accurate data analysis.
- Published 2 scientific papers in high-impact journals.
- Featured research project in the Berlin newspaper Tagesspiegel.
Universidade de São PauloOn-site
2016 - 2019
Academic Researcher
- Designed and implemented experimental protocols, ensuring precise data collection and analysis to support research objectives effectively.
- Conducted detailed statistical analysis of clinical and genomic data using SPSS.
- Compiled reports to communicate project results for funding agencies.
- Presented research outcomes at national and international conferences, earning one award for best presentation.
- Collaborated effectively with colleagues, contributing to the publication of 5 papers in scientific journals.
Education
Freie Universität Berlin | Max Planck Institute for Molecular Genetics
2019 - 2023
Doctor of Natural Sciences: Biochemistry
Universidade de São Paulo
2019 - 2016
Master of Science: Pharmacy
Pontifícia Universidade Católica do Paraná
2015 - 2011
Bachelor of Science: Biological Sciences
Skills
Statistical Analysis
Data Analysis
Data Visualization
Machine Learning
Python
R
SQL
Jupyter notebook
RStudio
MySQL
Visual Studio Code
Git
GitHub
Projects
Predicting Participant's Dropout Rates
github.combrunalos/clinical-trials-ml
Predicting participants dropout rates in vaccine clinical trials using machine learning. Deployed on Streamlit.
Side Project
Python
Jupyter Notebook
pandas
numpy
matplotlib
seaborn
scikit-learn
xgboost
Gene Expression Analysis
github.combrunalos/bcell-manuscript-figures
Gene expression analysis across various stages of B-lymphocyte activation and differentiation.
Research Project
Python
Jupyter Notebook
pandas
numpy
matplotlib
seaborn
scikit-learn
R
RStudio
tidyverse
dplyr
ggplot2