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👋 Hi there, I'm Francesco

🦸‍♂️ About me

I am a data scientist with 5+ years of experience, a mathematician by training, a passionate learner and an open source enthusiast.

I have in depth experience working on tabular data, time series, Bayesian statistic and mathematical optimization. I tend to prefer simple, scalable and understandable solutions as opposed to over-complex models when not necessary to bring value.

💼 Employer

  • Currently, I am a data scientist at HelloFresh🍋 in Berlin office.
  • Previously I worked a senior data scientist at Edison⚡ one of the leading Italian electric utility company. Here I was involved maily on mid and down stream projects on tabular data, time series, anomaly detection, and optimization.

💻 OSS and side projects

When I have some spare time on weekends I maintain few projects:

  • scikit-lego: since Sept. 2023 I am a maintainer of the project. The goal of the package is to allow to joyfully build new building blocks that are scikit-learn compatible. scikit-lego has 30k+ downloads a month
  • ISO Week Date: iso-week-date is a toolkit to work with strings representing ISO Week date in two formats: week YYYY-WNN and week date YYYY-WNN-D.
  • Timebasedcv: a python library that provides a cross validation strategies based on actual datetime values instead of indexes, of course compatible with scikit-learn cross validation API.
  • Compclasses: a python utility library to simplify composition (over inheritance).
  • Deczoo: a zoo for python decorators, a collection of decorators used on a daily basis.
  • Webapps (Also open source):
    • ATP Stats is a webapp providing tennis analytics and insights in a more colorful and intuitive manner with respect to the official ATP Tour.
    • Tabular Data Annotator a webapp to bulk label tabular data from a csv.

Both webapps are developed using python dash framework and deployed on heroku I need to migrate them to another hosting platform.

📫 How to reach me

The best way it to find me on linkedin.

🔧 Tech stack

  


                


             

Francesco Bruzzesi's Projects

archive icon archive

Archive of documents related to the Narwhals community building and support

awesome-polars icon awesome-polars

A curated list of Polars talks, tools, examples & articles. Contributions welcome !

formulaic icon formulaic

A high-performance implementation of Wilkinson formulas for Python.

functime icon functime

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

narwhals icon narwhals

Lightweight and extensible compatibility layer between Polars, pandas, cuDF, Modin, and more!

polars icon polars

Dataframes powered by a multithreaded, vectorized query engine, written in Rust

pomegranate icon pomegranate

Fast, flexible and easy to use probabilistic modelling in Python.

pynndescent icon pynndescent

A Python nearest neighbor descent for approximate nearest neighbors

river icon river

🌊 Online machine learning in Python

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