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Charles Bordet, Statistics Developer in Lyon, France
Charles Bordet

Statistics Developer in Lyon, France

Member since November 29, 2017
Charles is an experienced data scientist with a strong background in programming, machine learning, and statistics. He has helped a variety of clients in various industries, such as academic researchers, web startups, and Fortune 500 companies. His work spans from extracting and cleaning data to building data products backed with machine learning models.
Charles is now available for hire

Portfolio

Experience

  • Statistics, 6 years
  • R, 6 years
  • Data Science, 6 years
  • Pandas, 4 years
  • SQL, 4 years
  • Data Visualization, 4 years
  • Python 3, 3 years
Lyon, France

Availability

Part-time

Preferred Environment

Linux, GitLab, RStudio

The most amazing...

...project I've worked on is the build of a feature-extraction model to automatically identify key components of a PDF document (invoice, letter, and the like).

Employment

  • Machine Learning Researcher

    2019 - PRESENT
    Dexeo Technologie
    • Reviewed the scientific literature around existing models about analyzing and classifying text documents.
    • Analyzed needs in data to automatize with Machine Learning the existing solution to prevent manual labor.
    • Developed a Machine Learning model to automatically extract the most important features from a text document.
    Technologies: R, Text Mining, Machine Learning, Classification
  • R/Shiny Developer

    2019 - 2019
    Quote Velocity
    • Created an interactive dashboard to visualize and track data on a daily, weekly, and monthly basis.
    • Set up a system to improve detection of misqualified customers.
    • Self-hosted the dashboard as a web app on a remote server.
    Technologies: R, Shiny, Ggplot2, Plotly, DataTables
  • Data Scientist

    2018 - 2019
    Real Radiology
    • Deployed predictive models to anticipate the workload in radiology studies.
    • Created an interactive dashboard to visualize and track data on a daily basis.
    • Set up a system to show discrepancies between planned resources and predicted demand.
    Technologies: R, Caret, Shiny, Ggplot2, Plotly
  • Data Teacher

    2017 - 2019
    Professional Training
    • Trained professionals in R, Python, statistics, and machine learning.
    • Created online video courses in R, Python, deep learning, and artificial intelligence.
    • Enrolled more than 10,000 paying students.
    • Mentored students who were studying to become data analyst in OpenClassrooms.
    Technologies: R, Python, Statistics, Machine Learning, Deep Learning, Artificial Intelligence
  • R Developer

    2018 - 2018
    CNRS
    • Created a Shiny app for a research project in decision theory.
    • Optimized the app for conferences (short burst of users).
    • Added features such as account management, data entry, and visualization of probability distributions.
    • Deployed an updating system to make my client autonomous.
    • Deployed a Git server to easily clone the app for different uses.
    Technologies: R, Shiny, SQL, Git, Ggplot2, Azure
  • Research Assistant in Statistics and R

    2018 - 2018
    Aarhus University
    • Wrote text-mining algorithms.
    • Built topic models on UN resolution drafts.
    • Scored speeches of the UN General Assembly.
    • Classified EU Directorate-General based on legislative proposals.
    • Web scraped parliamentary questions of the Danish parliament, Bundestag documents, speeches of the UN General Assembly, and record details from the United Nations Digital Library.
    Technologies: Text Mining, Machine Learning, R, Web Scraping, AWS
  • Developer (R, Shiny)

    2018 - 2018
    BCG
    • Created and maintained a robust and user-friendly R Shiny app for a pricing strategy in retail during sales periods.
    • Enabled merchandisers to make scoring simulations.
    • Integrated Excel-like tables for easy manipulation of data.
    • Optimized the app to scale it to dozens of concurrent users.
    Technologies: R, Shiny, SQL, Git, Shell, Jenkins, Jira, Azure
  • Research Assistant in Statistics

    2018 - 2018
    EMMA Clinic
    • Implemented data analysis in a research laboratory for dermatology.
    • Wrote a descriptive analysis and multiple regression for a study on Vitiligo disease.
    • Implemented a statistical validation of a burden score on hand eczema disease.
    • Worked on a statistical study on relapse and impact on the adult acne productivity.
    Technologies: Statistics, R, Linear Models, LaTeX, Research
  • Data Scientist

    2017 - 2017
    Cargo Media
    • Set up a user-acquisition profitable strategy for a SaaS company.
    • Developed predictive models for RTB (Real-Time Bidding) channel.
    • Built predictive LTV models for new and existing users.
    • Created interactive dashboards in R Shiny to track KPIs.
    • Established indicators to improve fraud detection from affiliates.
    Technologies: Customer Analytics, Machine Learning, Survival Analysis, GLM, R, SQL, Shiny, AWS
  • Statistical Engineer

    2015 - 2017
    Sonovision
    • Created interactive dashboards in Shiny.
    • Built user-friendly desktop apps with Tcl/Tk.
    • Performed Weibull analysis for quality control.
    • Created interactive visualization tools to follow KPIs.
    • Automated recurrent tasks with R scripts.
    Technologies: Statistics, R, Shiny
  • PhD Student in Statistics (not completed)

    2013 - 2015
    Université Laval
    • Published academic papers.
    • Gave talks at conferences.
    • Mentored others in statistics.
    • Worked as a teaching assistant in statistics and R.
    • Consulted with graduate students concerning their statistics work.
    Technologies: Statistics, Machine Learning, Research, R

Experience

  • Freelance Work Showcase (Other amazing things)
    https://www.charlesbordet.com/en/

    This is my freelance website that showcases my work.

    Types of Work
    • Educational articles in data science
    • Case studies articles of my previous projects
    • Technical articles on R and Python

    It supports both English and French.

  • Deep Learning Projects (Python, Tensorflow and PyTorch) (Development)
    https://gitlab.charlesbordet.com/charles/deeplearning

    These are my personal projects that implement different deep learning algorithms with TensorFlow, Keras, and PyTorch.

    Project Types:
    • Predicting the churn rates at six months
    • Identifying objects in pictures
    • Predict stock price direction at day +1
    • Fraud detection
    • A recommender system

  • Artificial Intelligence Projects (Python, PyTorch) (Development)
    https://gitlab.charlesbordet.com/charles/artificial_intelligence

    This repo contains three reinforcement learning projects done with Python and PyTorch. They train an AI program in a closed environment to achieve specific goals.

    Projects:
    • Build a self-driving car
    • Create an AI playing Doom
    • Create an AI playing Breakout

Skills

  • Languages

    Python 3, SQL, R, Markdown, CSS, HTML
  • Frameworks

    RStudio Shiny, Selenium, Spark, Hadoop
  • Libraries/APIs

    Tidyverse, Ggplot2, Pandas, NumPy, Sklearn, Matplotlib, Spark ML, PySpark, TensorFlow
  • Tools

    Git, Handsontable, Dplyr, LaTeX, Shell, Plotly, sparklyr, Seaborn, Nginx, GitLab, DataTables, Sqoop, Docker Compose, GitLab CI/CD
  • Paradigms

    Data Science
  • Platforms

    Linux, AWS EC2, Docker
  • Storage

    PostgreSQL, MySQL, MongoDB
  • Other

    Statistics, Data Analysis, Data Visualization, Web Scraping, Computer Vision, Data Engineering, APIs, Data Analyst, Selenium Automation, Machine Learning

Education

  • PhD (not completed) degree in Statistics
    2013 - 2015
    Université Laval - Québec, Canada
  • Master's degree in Statistics
    2011 - 2013
    Université de Strasbourg - Strasbourg, Alsace, France
Certifications
  • Deep Learning
    FEBRUARY 2019 - PRESENT
    Coursera
  • Spark & Hadoop Developer
    OCTOBER 2018 - OCTOBER 2020
    Cloudera
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