Corentin Martel, Developer in Rougemont, France
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Corentin Martel

Verified Expert  in Engineering

Data Scientist and Machine Learning Developer

Rougemont, France
Toptal Member Since
September 27, 2018

Corentin earned a master's degree in engineering from Arts et Métiers ParisTech. He started coding in Python in 2014 and never stopped. Working as a freelancer since 2016, Corentin specializes in data mining and custom development of machine learning and deep learning-based products. Passionate about data science, he also teaches students in an online MSc program. Corentin enjoys working on new topics and learning from others.


Python, Recommendation Systems, Generative Pre-trained Transformers (GPT)...
Corelyo (Freelance)
Amazon Web Services (AWS), Machine Learning, Data Science, DataViz, OpenCV..., with Corelyo (Freelance)
Recurrent Neural Networks (RNNs), Deep Learning, DataViz, Pandas, Keras, Python...




Preferred Environment

PyCharm, Anaconda

The most amazing...

...thing I've developed is a recommendation algorithm for a B2B eCommerce website with over 30,000 products using recurrent neural networks.

Work Experience

Data Scientist

2021 - PRESENT
  • Developed an unsupervised recommendation algorithm for an on-demand video platform with over 200 k movies.
  • Worked on data cleansing and feature engineering (e.g. identify duplicates movies and staff, and create collections of movies).
  • Worked on NLP: description-based similarity in multi-languages.
  • Deployed an interactive app to test and optimize the model.
Technologies: Python, Recommendation Systems, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), DataViz, Data Mining, Streamlit, Docker, SQL

Data Scientist

2016 - PRESENT
Corelyo (Freelance)
  • 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.
  • 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.
  • Worked on an exploratory data analysis on tennis data to discover the importance of the first serve percentage in a game, and more broadly what can give a player an edge. I wrote a report with visualisations and interpretation of my results.
  • 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.
Technologies: Amazon Web Services (AWS), Machine Learning, Data Science, DataViz, OpenCV, Scikit-learn, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNN), Deep Learning, Data Analysis, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Keras, Python, Data Analytics, SQL, Tableau

Data Scientist

2019 - 2019, with Corelyo (Freelance)
  • Designed from scratch a recommendation engine for a B2B eCommerce website selling hardware to contractors (30,000 products).
  • Analyzed customer behavior to better understand the need and choose the most efficient algorithm. The best algorithm largely depends on the clients: Do they buy the same things each time and are there buying patterns?
  • Tested several architectures and models, including an RNN-based deep learning model with embedding; also set up metrics and tried various algorithms and data processing to improve it.
  • Set up an API to serve recommendations, using Flask and Docker.
  • Implemented a Docker container for retraining the model on a regular basis.
Technologies: Recurrent Neural Networks (RNNs), Deep Learning, DataViz, Pandas, Keras, Python, Recommendation Systems

Data Scientist

2018 - 2018
Doctegestio, with Corelyo (Freelance)
  • Implemented a machine learning algorithm for document classification (1.5 million documents to classify in 500 categories).
  • Created dataset using OCR (optical character recognition) to extract features from PDF and scans, feature engineering, and cleaning for bad quality scans.
  • Tested several models over multiple Agile iterations; we first tried with 10,000 documents in five categories and then we iterated when the model was working.
Technologies: Pandas, Tesseract, OCR, Scikit-learn, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Python, Text Classification, Text Categorization

Data Scientist

2017 - 2017, with Corelyo (Freelance)
  • Created a dataset of website categories using a Python scraper on a yellow-page website, to collect thousand of websites URLs for each category.
  • Tested several NLP pipelines and models to classify new websites based on content, by setting a metrics and working to optimize it over several iterations.
  • Deployed the selected model in production using a Flask API and Docker.
Technologies: Machine Learning, Flask, Pandas, Scikit-learn, Python, Text Classification, Text Categorization

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, Data Analytics

Website Classification Algorithm
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
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.
2010 - 2013

Master of Science Degree in General Engineering

Arts et Métiers ParisTech - Paris, France


Machine Learning

Stanford University via Coursera


XGBoost, Pandas, NumPy, Scikit-learn, Keras, Matplotlib, SciPy, Natural Language Toolkit (NLTK), OpenCV, TensorFlow


DataViz, DigDash, Tableau, Seaborn, Jupyter, Plotly, PyCharm, Git, GitHub


Flask, Streamlit


Python, Python 2, Python 3, SQL


Data Science




Windows, Anaconda, Ubuntu, Jupyter Notebook, Docker, Amazon Web Services (AWS)


Clustering, Regression, Data Visualization, Data Mining, Machine Learning, Data Analysis, Data Analytics, Deep Learning, Artificial Intelligence (AI), Convolutional Neural Networks (CNN), Image Processing, Recommendation Systems, Natural Language Processing (NLP), Computer Vision, Text Classification, Text Categorization, Generative Pre-trained Transformers (GPT), OCR, Tesseract, Recurrent Neural Networks (RNNs)

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