✤ Current role: data scientist researcher
✤ Research interests: data science statistics data visualization XAI
✤ Get in touch:
→ martinadossi.hello[@]gmail.com
→ LinkedIn | Behance | Instagram | GitHub
→ I am a data scientist and statistician with +5 years of working experience.
→ I am strongly interested in data visualization and information design as a way to translate, share and illuminate complex phenomena and enhance accessibility for a broader and less technical audience.
→ Over the years, I have gained expertise in extracting valuable insights from datasets and possess the ability to independently managing all phases of data analysis, including data understanding, statistical analysis, data cleaning, and modelling. I consider data visualization a powerful means to effectively communicate such findings in a more engaging manner, prioritizing rigor and fidelity to the underlying data. My interest in information design principles lies in their key role in converting charts into actionable knowledge, empowering data-driven decision-making processes.
→ Lately, I've been particularly drawn to exploring the applications of data visualization in machine learning and AI. I'm fascinated by how these techniques can enhance the accessibility and clarity of models throughout their development—from preliminary data analysis to internal mechanisms, explainability, and deployment. Additionally, I'm keen to delve deeper into interactive visualizations, building on my experience with tools like Streamlit, which I use both professionally and in personal projects.
A chronological list of things I find and like
In 2024, I started collecting small, personal data on a daily basis –how I felt and with what intensity, where I was, whether I watched a movie, had a migraine, went to the office, and more. Working with my personal data is a project I had in mind for a long time, and I’m happy I finally brought it to life! ✨
I’ve been tracking my feelings using the emotion wheel (see below) as main reference. The app is built with Streamlit (an open-source Python library) –you can explore it by clicking on the tab below!
https://pixelyear-dataviz.streamlit.app/?embed=true
In this project, my aim is to explore and dig deeper into topics starting from charts I come across while navigating the web –charts that I would have designed slightly differently. The idea is to experiment with multiple alternatives and find the visualization that works best for a given dataset and context.
To support the series, I’m using Marimo, an interactive Python notebook I simply find fantastic. It’s reactive, clean, and designed to make both exploration and storytelling seamless. In these notebooks, you can not only see the charts and analysis but also inspect the underlying Python code (hidden by default for a cleaner experience).
Explore the first notebook here:
https://martidossi.github.io/data_viz_makeover/apps/1_when_european_fly_nest.html