I am passionated about the science behind data acquisiton and analysis. I started out usinf python for bioinformatics during my BSc, moved on to metabolomics (study of metabolite data) with R throughout my internship (developed an R workflow for that kind of data, that turned out to be a full R package: PipMet!).

Then, I went to back to python and Excel (VBA/Macros) to workout clinical trials data as a Data Assistant.

After, a two-year MSc provided me with a lot of time to investigate huge amounts of (very complex) chemical data, using all tools I could put my hands on (python, R, MATLAB, SQL, viz tools ...).

Currently, I decided to move out from academia and bring all my academic strenghts to the business world. I aspire to apply the structured scientific thought to the on-going, real world data as a Data Scientist.

My focus is more than just running code. It is to understand business logic, structure the analysis, discuss data, results and algorithms performance, to deliver actional values, wheter it is in Finance, Reatail ou Tech.

• 🔭 Current focus: Developing Power BI projects and advancing Python skills for Machine Learning.
• 💼 Differential: Fast learning capability combined with critical, scientific thinking.
• 🎯 Goal: To act as a Data Analyst or Scientist in dynamic, data-driven environments.

Data Analysis & Engineering

Visualization & Business Intelligence