Nicolas Debaene, Machine Learning Developer in Paris, France
Nicolas Debaene

Machine Learning Developer in Paris, France

Member since October 18, 2019
With a master of science degree in engineering and a specialization in data science from Telecom ParisTech, Nicolas has been solving concrete business cases for three years using machine learning and data mining. His experience in the eCommerce, banking, and consulting sectors give him a very strong technology portfolio and a deep understanding of different business types.
Nicolas is now available for hire


  • BNP Paribas
    Git, Linux, Keras, PyTorch, NumPy, Pandas, Scikit-learn, SQL, Python
  • CDiscount (eCommerce)
    Git, Linux, Keras, PyTorch, NumPy, Pandas, Scikit-learn, SQL, Python
  • Wavestone
    Git, Linux, Keras, NumPy, Pandas, Scikit-learn, Python



Paris, France



Preferred Environment

PyCharm, Jupyter Notebook, SQL, Ubuntu, Windows, Python

The most amazing... science solution I've built was a credit scoring model that decreases default by 10 million Euros/year for a large French eCommerce company.


  • Data Scientist

    2019 - 2020
    BNP Paribas
    • Provided artificial intelligence tools to bankers working in BNP Paribas Corporate and Institutional Banking.
    • Detected potential churners by predicting the evolution of sales of Forex products (time series forecasting methods like ARIMA and Auto-Regressive Neural Network).
    • Built a recommender engine to recommend financial products to BNP Paribas's clients using collaborative filtering (CF) methods (deep collaborative filtering).
    • Participated in the development of an optical character recognition tool to extract information from invoices in image format (regional neural network, recurrent neural network).
    • Developed a text classification tool for a CRM system to score descriptions of meetings happening between a banker and a client of the bank (high score means the description is explicit and informative).
    • Participated in the migration of ETL pipelines (used to create KPI dashboards for the bank) from Alteryx to Spark.
    Technologies: Git, Linux, Keras, PyTorch, NumPy, Pandas, Scikit-learn, SQL, Python
  • Data Scientist

    2017 - 2018
    CDiscount (eCommerce)
    • Designed and developed an accurate, useful, and stable credit risk model for payment in four installments on the company's selling platform.
    • Initiated the production of new, improved credit scoring models every three months.
    • Optimized credit scoring models to score in real-time every customer buying on the website (one million visits per day, implied building a very fast computing model).
    • Integrated new data sources and solutions into credit risk strategies.
    • Interpreted data science models and gave business recommendations to senior leaders.
    Technologies: Git, Linux, Keras, PyTorch, NumPy, Pandas, Scikit-learn, SQL, Python
  • Junior Data scientist

    2017 - 2017
    • Created a predictive maintenance model for a transport company using machine learning (data cleaning, gradient boosting trees and detecting very rare events).
    • Created a benchmark of text classification methods with the purpose to develop a chatbot for the company.
    • Crunched and analyzed data for a French national social organization to detect loss of money in allowances distribution.
    Technologies: Git, Linux, Keras, NumPy, Pandas, Scikit-learn, Python


  • Customer Churn Detection (Development)

    While working at BNP Paribas, I developed a statistical and machine learning model to detect potential churners within clients of the bank.
    I developed a method based on time series forecasting to predict the amount of forex transfer each client would request in the next year. The bankers could then take steps to retain the client. I developed a statistical time series forecasting (ARIMA model) and used deep learning auto-regressive models to achieve better performance.


  • Languages

    Python, SQL
  • Libraries/APIs

    Matplotlib, Scikit-learn, Pandas, NumPy, Keras, PyTorch, TensorFlow, PySpark
  • Paradigms

    Data Science, Agile Software Development, Unit Testing, Scrum
  • Other

    Artificial Intelligence (AI), Data Analyst, Data Analytics, Data Visualization, Machine Learning, Data Mining, Deep Learning, Credit Risk, Recommendation Systems, Forecasting, Natural Language Processing (NLP), Computer Vision
  • Frameworks

  • Tools

    Git, Jupyter, IPython, Tableau, PyCharm
  • Industry Expertise

  • Platforms

    Ubuntu, Jupyter Notebook, Linux, Windows


  • Master's degree in Computer Science
    2015 - 2017
    Telecom ParisTech - Paris, France
  • Bachelor's degree in Mathematics
    2012 - 2015
    Telecom ParisTech - Paris, France

To view more profiles

Join Toptal
Share it with others