Data Scientist


Highly Simplified Background

  • Mathieu Anderhalt

    I was born in Toulouse, in the south of France. I spent there the first 21 years of my life before moving to Paris.

  • 2005

    Literature and Social Sciences

    Higher School Preparatory Class in Litterature and Social Sciences.

  • 2008

    ENSAE ParisTech

    The ENSAE (Ecole Nationale de la Statistique et de l'administration Economique) is one of the leading French institutions of higher learning in the fields of statistics, economics, finance and actuarial science. It is one of the founder member of the Paris Institute of Technology

  • 2012

    Freelance Data Scientist

    Freelance consultant in Data Sciences: Data modeling, Machine Learning, Business Intelligence, Data visualization + Contributions to the open source community in many fields related to Data Sciences.

  • 2012

    EDF R&D

    Manager of a project on Climate Change, Environement and Power Plants. Team of 15 contributors.

  • 2016

    Creating Données Brutes

    Consulting company in Data Sciences and data valuation for industry.


What I can do and what I like to do!


I like working and building new activities! Brainstorming, initiating projects, planning tasks, controlling, motivating and closing the work of a team to achieve goals! I like technical activities and communication, working with people and sharing adventures!

Data Science

Analyzing data is a passion! Finding causalities and effects, trying to give the data a meaning, explaining and understanding. In one word, making the data more valuable. Python is an incredible partner for this. Combined with a higher theoretical knowledge in Statistics, Algebra and Machine Learning, there is nowhere you can't go!

Data Management

I started to use Big Data oriented and/or schema-less databases like MongoDB and Hadoop a few years ago. I like the power of distributed algorithms that scale to Big Data, full text search features and geospatial queries. I'm very familiar with SQL oriented database systems such as PostgreSQL.

Data Visualization

It is nice to know how to analyze and handle with data. But to bring data to life and to make it beautiful, package it to a web App! I like to use Node or Django to build the core of interactive web applications. For visualizations, I could spend days and days creating charts and infographics with d3. These kinds of libraries help us to make the data science an Art!


Companies I worked with or for