Francesco Bruzzesi, Developer in Berlin, Germany
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Francesco Bruzzesi

Verified Expert  in Engineering

Data Scientist and Developer

Berlin, Germany
Toptal Member Since
May 12, 2022

Francesco is a data scientist with over four years of experience, a mathematician by training, and a passionate learner. He is especially interested in bringing value to a team or product, which, in his experience, has often translated to preferring simple, scalable, and understandable solutions instead of overcomplex models when unnecessary.


Python, Pandas, NumPy, PyTorch, Scikit-learn, Amazon Web Services (AWS), SQL...
Python, NumPy, Pandas, Spark, Azure, Databricks, SQL...




Preferred Environment

Linux, Visual Studio Code (VS Code), Windows Subsystem for Linux (WSL)

The most amazing...

...things I've developed are multiple web apps for internal use so that business experts can operate and interact with ML models and the results.

Work Experience

Senior Data Scientist

2020 - PRESENT
  • Analyzed and forecasted customer behavior to monitor and optimize debt collection and churn prediction processes.
  • Developed end-to-end pipelines to forecast time series plant production with multiple time horizons.
  • Coached and mentored new hires, guiding them through a beautiful journey into the data world.
Technologies: Python, Pandas, NumPy, PyTorch, Scikit-learn, Amazon Web Services (AWS), SQL, Docker, Kubernetes, Visual Studio Code (VS Code), Spark, Machine Learning, Data Science

Data Scientist

2018 - 2020
  • Optimized internal processes of an automotive company, in order to build data-driven insights from vehicle sensor data. In particular, I reduced ETL and forecast time from 12 down to 1.5 hours, which led to eight times faster implementation.
  • Provided in-depth analysis and created an ad-hoc tool to monitor quantitative team KPIs and trigger forecasting models for a utility company.
  • Performed exploratory data analysis, hypothesis testing, data preparation and preprocess for statistical and machine learning modeling. I also assisted in architecture migration to big data solutions, premise to cloud, in a telco company.
Technologies: Python, NumPy, Pandas, Spark, Azure, Databricks, SQL, Visual Studio Code (VS Code), Scikit-learn, Machine Learning, Data Science

Deczoo is a small Python library, a zoo for decorators. I developed and currently maintain the library.

There are many great decorators that I found myself implementing over and over in different projects. The hope is to gather them and use this codebase.

Tabular Data Annotator Web App

Data Annotator is an open source web app for annotating tabular data from a CSV file. It was originally intended for time series data, hence the repo's name and URL name.

It exists because countless times a business expert or myself had to annotate tabular data and this solution made it faster.

Tennis Stats Web App

Tennis Stats is a web app providing tennis analytics and insights in a more colorful and intuitive manner with respect to the official ATP Tour website. It uses open source data from the amazing Jeff Sackmann GitHub repository.
2016 - 2018

Master's Degree in Mathematics

The University of Milan - Milan, Italy

2016 - 2018

Master's Degree in Mathematics

University of Duisburg-Essen - Essen, Germany

2013 - 2016

Bachelor's Degree in Mathematics

University of Bologna - Bologna, Italy


NumPy, Pandas, Scikit-learn, PyTorch


Python, SQL


Data Science


Flask, WebApp, Spark


Linux, Visual Studio Code (VS Code), Azure, Databricks, Amazon Web Services (AWS), Docker, Kubernetes


Mathematics, Statistical Methods, Data Modeling, Machine Learning, Windows Subsystem for Linux (WSL), Probability Theory, Discrete Mathematics, Number Theory

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