Corentin Martel, Data Scientist and Developer in Lyon, France
Corentin Martel

Data Scientist and Developer in Lyon, France

Member since August 29, 2018
From Arts et Métiers ParisTech, Corentin earned a master's degree in engineering. In 2014, he started coding in Python, and he's never stopped. Working as a freelancer since 2016, Corentin specialized in both data mining and custom development of machine learning and deep learning-based products. Passionate about data science, Corentin also teaches students of an online MSc program.
Corentin is now available for hire


  • Corelyo
    Python, Sklearn, Keras, NLP, Data Analysis
  • LML



Lyon, France



Preferred Environment

Anaconda, PyCharm

The most amazing...

...thing I've developed is a recommendation algorithm for a B2B e-commerce website with over 30k products using recurrent neural networks.


  • Data Scientist

    2016 - PRESENT
    • Implemented a machine learning algorithm for document classification. The full pipeline included OCR (optical character recognition) to extract features from pdf and scans, feature engineering and cleaning for bad quality scans, and an occurrence-based classification model.
    • Worked on various analysis and business intelligence (BI) projects. This included assessing the impact of ads on users of an eShop, creating a complete set of KPI/charts for a CRM editor, and building dashboards for HR indicators.
    • Mentored students for openclassrooms and hold weekly student appointments to guide them through their data science journeys.
    • Designed from scratch a recommendation engine for a B2B eCommerce website selling hardware to contractors. Tested several architectures and models, and set up an API to serve recommendations when needed. Also implemented a docker container for re-training the model on a regular basis.
    • Developed an unsupervised image classification algorithm based on image similarities, applied on social network images. The objective was to evaluate the social engagement generated by each type of image, to optimize the social presence of my client.
    • Worked on an exploratory data analysis on tennis data, aiming to discover the importance of the first serve percentage in a game, and more broadly what can give a player an edge over its opponent. The deliverable was a report with mostly visualisations and interpretation of my results.
    • Implemented a clustering API for SEO keywords, based on the SERP results of these keywords. The goal was to make connections between keywords that are syntactically very different but of same meaning.
    • Designed, for a growth hacking agency, an algorithm to find common traits between prospects and clients and used this to prioritize prospects and find out which product they were most likely to be interested in.
    Technologies: Python, Sklearn, Keras, NLP, Data Analysis
  • Research Engineer

    2014 - 2016
    • Developed a Python module for testing materials which enabled PhD students to quickly design custom setups with synchronized sensors, camera, and actuators.
    • Conducted some tests on my own and extracted useful data from the measures.
    Technologies: Python


  • Website Classification Algorithm (Development)

    I designed a website classification algorithm for my client. This algorithm analyzed the content of a website and classified it in one of the classes that we designed with my client.

    This is currently in production so you can test it in real time via the link attached.

  • Recommendation Algorithm (Development)

    I designed the recommendation engine from scratch, for a B2B website selling equipment and hardware to construction professionals.

    The website is in French, but the recommended items are the one labeled "Nos clients achètent aussi," below any product.


  • Languages

    Python, Python 2, Python 3, SQL
  • Frameworks

  • Libraries/APIs

    Sklearn, XGBoost, Pandas, NumPy, Scikit-learn, Keras, Matplotlib, SciPy, NLTK, TensorFlow
  • Tools

    DataViz, DigDash, Tableau, Seaborn, Jupyter, Plotly, Git, GitHub
  • Paradigms

    Data Science
  • Other

    Clustering, Regression, Data Visualization, Data Mining, Machine Learning, Data Analysis, Data Analytics, Deep Learning, Artificial Intelligence (AI), Convolutional Neural Networks, Image Processing, Natural Language Processing (NLP), Computer Vision
  • Platforms

    Windows, Anaconda, Ubuntu, Jupyter Notebook, Docker


  • Master of Science degree in General Engineering
    2010 - 2013
    Arts et Métiers ParisTech - Paris, France


  • Machine Learning
    JULY 2016 - PRESENT
    Stanford University via Coursera

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