Benjamin Larrousse, Data Science Developer in Paris, France
Benjamin Larrousse

Data Science Developer in Paris, France

Member since July 10, 2020
Benjamin is a talented senior data scientist who earned a Ph.D. in applied mathematics and has a strong focus on optimization and game theory. He uses expert-level analytics skills to deliver data and predictions, enabling clients to make strategic decisions that benefit profits as well as customers. He recently implemented Recurrent Neural Networks to predict purchases with 95% accuracy. Benjamin is passionate about science and loves using mathematics to make the world a better place.
Benjamin is now available for hire


    Pandas, Scrum, Google Cloud Platform (GCP), BigQuery, Jupyter Notebook, SQL...
    SQL, Matplotlib, Scikit-learn, Python



Paris, France



Preferred Environment

Google Cloud Platform (GCP), BigQuery, Scikit-learn, SQL, Keras, TensorFlow, Jupyter Notebook, Python

The most amazing...

...Recurrent Neural Network I've implemented used TensorFlow on the Google Cloud Platform to predict the probability of purchases with 95% accuracy.


  • Senior Data Scientist

    2017 - 2020
    • Implemented a Recurrent Neural Network to predict purchases with 95% accuracy.
    • Designed and successfully put into production a recommender system for retailers.
    • Finalized various proof-of-concept projects to help retailers make use of their data.
    Technologies: Pandas, Scrum, Google Cloud Platform (GCP), BigQuery, Jupyter Notebook, SQL, TensorFlow, Keras, Python
  • Data Scientist

    2015 - 2015
    • Uncovered general trends for the first mobile game of the company with in-depth, descriptive statistics.
    • Developed churn prediction and other mathematical applications to improve mobile games.
    • Managed user acquisition on Facebook ads networks and Google Adwords for four mobile apps in over 20 countries.
    Technologies: SQL, Matplotlib, Scikit-learn, Python


  • A Data Perspective: Is it Possible to Defend Against Messi?

    Analysis of the Messi biography dataset helped uncover insights about how to defend against him. Data exploration involved 15 years of data with Python (Plotly for data visualization) and advanced football metrics. Workflow occurred with Jupyter Notebooks, including one for unit testing.


  • Languages

    Python 3, SQL, Python
  • Paradigms

    Data Science, Data-driven Methodology, Scrum
  • Other

    Mathematics, Game Theory, Machine Learning, Research, Information Theory, Optimization, Deep Learning, Artificial Intelligence (AI), Algorithms, Football, Sports, Analytics
  • Libraries/APIs

    TensorFlow, Keras, Scikit-learn, Pandas, Matplotlib
  • Tools

    TensorBoard, MATLAB, BigQuery
  • Platforms

    Jupyter Notebook, Google Cloud Platform (GCP)


  • Ph.D. in Applied Mathematics
    2011 - 2014
    Université Paris Sud XI - Paris, France


  • Introduction to Football Analytics
    APRIL 2020 - PRESENT
  • Deep Learning with TensorFlow
    MARCH 2017 - PRESENT
    Big Data University
  • Data Science Methodology
    Big Data University
  • Machine Learning
    APRIL 2015 - PRESENT

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