CV 2

resume.json

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  "basics": {
    "name": "Yannick Caillaud",
    "label": "Data Scientist @Betclic-Group",
    "image": "",
    "email": "yannick.caillaud@hotmail.fr",
    "phone": "",
    "url": "",
    "summary": "Passionate about Machine Learning, Data Mining and Data Science in general.\nEnjoy create value based on not enough exploited data: from POC to MVP to Production, from quick-wins to R&D challenge.\n[Kaggle](https://www.kaggle.com/kinnay) competition contributor.",
    "location": {
      "countryCode": "FR",
      "address": "",
      "city": "Bordeaux"
    },
    "profiles": [
      {
        "network": "LinkedIn",
        "username": "yannick-caillaud",
        "url": "https://www.linkedin.com/in/yannick-caillaud/"
      },
      {
        "url": "https://github.com/YCaillaud-betclic",
        "username": "YCaillaud-betclic",
        "network": "github"
      }
    ]
  },
  "work": [
    {
      "name": "Betclic Group",
      "position": "Data Scientist",
      "startDate": "2020-03-31",
      "endDate": "2022-05-31",
      "highlights": ["python, scikit-learn, tensorFlow, keras, smote, boruta, shap, jupyter notebook, pycharm", "AWS Sagemaker, S3, git, github, SQL Server, Snowflake, Airflow, Talend Management System", "Agile, Jira Ticket"],
      "summary": "**Legal and Compliance**\n• Responsible/Safer gaming: help the responsible gaming team to focus on the customer the more at risk.\n• Money laundering: detection of suspect behaviours in customers action.\n\n**Customer Relationship Management**\n• Personalisation of bet offer: adapt for each customer the contains of emailing campaign.\n• Churn and lapse: detection of potential churn in a retention purpose.\n\n**Acquistion**\n• Customer Lifetime Value : prediction of the customer value potential to adapt and improve the acquistion of new customers.\n\n**Trading**\n• Turnover Prediction: Anticipate the amount of turnover expected depending on the sport calendar.\n• Bet Liabilities: Inform traders about the current liabilities in order to adapt the odds accordingly.\n\n**Management**\n• Supervision of trainees and junior Data Scientist.",
      "url": "https://betclicgroup.com/",
      "location": "Bordeaux, France"
    },
    {
      "name": "Data University France - Institut de science des données",
      "position": "Data Science Teacher",
      "startDate": "2018-09-30",
      "endDate": "2020-04-30",
      "highlights": ["Teaching, Data Science, Data Analyst, python, R"],
      "summary": "Teached to multiple class through theorical and practical courses the following skills \n• Computer Science: scientific usage of python and R\n• Ethic & Data Science\n• Define and understand the changes brought about by the GDPR\n• Basics of machine learning and data cleaning",
      "url": "https://datauniversity.fr/",
      "location": "Bordeaux, France"
    },
    {
      "name": "Thales",
      "position": "Data Scientist",
      "startDate": "2017-02-28",
      "endDate": "2020-03-31",
      "highlights": ["python, Spark, PySpark, Keras, Scikit-Learn, TensorFlow, Jupyter Notebook", "Big Data: ElasticSearch, Kibana", "Mockup: Bokeh, Power Bi", "Presentation, Agile"],
      "summary": "**Predictive Maintenance**\n• Analyze the potential causes of failures of aeronautical equipment\n• Predict failures of aeronautical equipment\n• Write patents\n\n**Anomalies Detection**\n• Time series on cable car lines\n• Time series for maritime surveillance\n\n**NLP**\n• Extract keywords from a free text field\n• Create an intelligent search engine\n• Design a chatbot (MVP project)\n\n**Service Compagny needs**\n• Drafting response to a call for tenders\n• Translate clients need to technical description\n• Knowing how to quantify the right amount of working time before the start of a project\n• Compliance with deadline",
      "url": "https://www.thalesgroup.com/fr",
      "location": "Bordeaux, France"
    },
    {
      "name": "watiz",
      "position": "Data Scientist Junior",
      "startDate": "2016-10-31",
      "endDate": "2017-02-28",
      "highlights": ["Neural network framework: Keras, TensorFlow, Caffe"],
      "summary": "Re-identification of people in Deep Learning during my final year project in collaboration with the startup Watiz.\n**Missions**\n• Read and synthesize scientific papers\n• Realize a state of the art by highlighting promising ideas\n• Use Keras and Caffe to create neural networks",
      "url": "https://watiz.io/",
      "location": "Paris, France"
    },
    {
      "name": "Polytechnique Montréal",
      "position": "Data Mining Teaching Assistant",
      "startDate": "2016-06-30",
      "endDate": "2016-08-31",
      "highlights": ["python, R, R Studio, Computer Science, Teacher, Keras, Scikit-Learn"],
      "summary": "Development of Data Mining TDs.\nAssignments:\n• Understand the Data Mining courses.\n• Design algorithms generating exercises to learn the following Data Mining methods: Association Rule, Segmentation, Trees, Bayesian Networks and Neural Networks\n• Allow regeneration of different data from one year to the next\n• Create the tutorial sheets and test the exercises",
      "url": "https://www.polymtl.ca/",
      "location": "Montréal, Canada"
    }
  ],
  "volunteer": [],
  "education": [
    {
      "institution": "GameCare",
      "area": "Interaction and motivating behaviour change training",
      "studyType": "Social responsibility",
      "startDate": "2021-11-01",
      "endDate": "2022-11-01",
      "score": "",
      "courses": ["Safe Gambling", "Behaviour change", "Interact with customers"]
    },
    {
      "institution": "Thales",
      "area": "Trainer training",
      "studyType": "Teaching",
      "startDate": "2019-07-01",
      "endDate": "2019-07-04",
      "score": "",
      "courses": ["Teach", "Make presentations"]
    },
    {
      "institution": "Télécom SudParis",
      "area": "Mathématiques et informatique",
      "studyType": "Ingénieur du numérique ",
      "startDate": "2014-12-31",
      "endDate": "2017-12-31",
      "score": "",
      "courses": ["Computer Science", "Mathematics", "Artificial Intelligence"]
    },
    {
      "institution": "Lycée Camille Julian",
      "area": "Scientific",
      "studyType": "Baccalauréat",
      "startDate": "2012-12-31",
      "endDate": "2014-12-31",
      "score": "",
      "courses": []
    }
  ],
  "awards": [
    {
      "title": "18th/913 (Silver Medal - Top 2%) Abstraction and Reasoning Challenge",
      "date": "2020-08-31",
      "awarder": "Kaggle",
      "summary": "Create an AI capable of abstraction, i.e. solving reasoning tasks it has never seen before ([challenge link](https://www.kaggle.com/c/abstraction-and-reasoning-challenge))."
    },
    {
      "title": "Machine Learning",
      "date": "2016-10-31",
      "awarder": "Coursera",
      "summary": "Andrew Ng, University of Stanford ([link](https://fr.coursera.org/learn/machine-learning))."
    },
    {
      "title": "Top 12% on Coding Game",
      "date": "2022-02-01",
      "awarder": "Coding Game",
      "summary": "Solve algorithm problem with Python and C++ code ([profile link](https://www.codingame.com/profile/5317632726e780a76259f142a81d531c5165441))."
    }
  ],
  "publications": [
    {
        "name": "Patent: Procédé et système d'évaluation d'un système de prédiction de dépose d'un équipement",
        "publisher": "Thales Group",
        "releaseDate": "2021-10-01",
        "url": "https://worldwide.espacenet.com/patent/search/family/070804806/publication/FR3108744A1?q=pn%3DFR3108744A1"
    }
  ],
  "skills": [
    {
      "name": "Data Science",
      "level": "5",
      "keywords": ["Machine Learning", "Data Analysis", "Data Mining", "Statistics", "Scikit-learn", "Pandas", "Numpy", "Tensorflow", "Keras", "Shap", "Jupyter Notebook", "Pycharm"]
    },
    {
      "name": "Programming",
      "level": "5",
      "keywords": ["Python", "SQL", "C++", "C", "Git/Github", "Scala", "R", "Java", "Linux"]
    },
    {
      "name": "Big Data",
      "level": "5",
      "keywords": ["Spark", "Spark Streaming", "PySpark", "AWS Sagemaker", "S3", "ElasticSearch"]
    }
  ],
  "languages": [
    {
      "fluency": "Full Professional",
      "language": "English"
    },
    {
      "fluency": "Native Speaker",
      "language": "French"
    },
    {
      "fluency": "B1",
      "language": "German"
    }
  ],
  "interests": [
      {
        "name": "Triathlon",
        "keywords": ["Cycle", "Swim", "Run", "Beyond the limit"],
        "description": ""
      },
     {
        "name": "Japanese Animation",
        "keywords": ["Anime", "Manga"],
        "description": ""
      },
     {
        "name": "E-Sport",
        "keywords": ["CS-GO", "HearthStone"],
        "description": ""
      }
    ],
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