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Julien St-Pierre Fortin, Software Developer in Montreal, QC, Canada
Julien St-Pierre Fortin

Software Developer in Montreal, QC, Canada

Member since November 13, 2019
Deploying software solutions in the realm of data is Julien's expertise. He is passionate about helping clients create innovative products and gain valuable insights from data. He genuinely cares about his clients and goes above and beyond to ensure highly successful products.
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Portfolio

  • Coveo
    C#, MySQL, .NET, Object-oriented Programming (OOP), APIs, Salesforce
  • Mino Games
    Google Cloud, SQL, Scikit-learn, Pandas, Python, Data Science
  • Gameloft
    Linux, Vue, Docker, Jupyter Notebook, Keras, TensorFlow, Matplotlib...

Experience

Location

Montreal, QC, Canada

Availability

Part-time

Preferred Environment

Visual Studio Code (VS Code), Sublime Text, Git, MacOS, Visual Studio, ReSharper, GitKraken, Jira

The most amazing...

...project I've built is a data-intensive REST API to feed an interactive art installation with real-time financial analytics.

Employment

  • Software Developer

    2019 - PRESENT
    Coveo
    • Improved data access security of indexed Salesforce data.
    • Monitored multiple deployments stress-free with Hosted Graphite and LaunchDarkly feature flags.
    • Tracked bugs with Sentry and Kibana and managed work in Jira.
    Technologies: C#, MySQL, .NET, Object-oriented Programming (OOP), APIs, Salesforce

  • Data Scientist

    2019 - 2019
    Mino Games
    • Built machine learning models from cohort KPIs to get early feedback on marketing activity, such as the likelihood of acquired cohorts profitability.
    • Developed revenue forecast models using curve-fitting methods.
    • Built dashboards to monitor user behavior with SQL, BigQuery and Mode Analytics.
    • Developed a Python library to streamline the machine learning process.
    Technologies: Google Cloud, SQL, Scikit-learn, Pandas, Python, Data Science

  • Data Scientist

    2016 - 2019
    Gameloft
    • Built machine learning models based on user behavior to predict cohorts LTV and profitability using scikit-learn and TensorFlow.
    • Co-developed many data science tools, a model factory, and APIs with Pandas and Flask.
    • Built an automated task scheduler using Apache Airflow.
    • Researched user dynamics spanning multiple products with Markov chains and recurrent neural networks.
    • Co-developed UI in Vue.js to visualize model predictions.
    Technologies: Linux, Vue, Docker, Jupyter Notebook, Keras, TensorFlow, Matplotlib, Scikit-learn, Pandas, Python, Data Science

  • Research Assistant

    2014 - 2015
    INRS
    • Developed deep learning models with MATLAB to predict water temperature from meteorological data to support engineering at Beauharnois hydropower plant in Quebec.
    • Conducted research on the development of a network for measuring and collecting water temperature data from covariates. We used mutual information and dimensionality reduction methods using MATLAB.
    • Conducted web scraping of the Statistics Canada website to obtain meteorological data using Python.
    Technologies: Windows, Deep Learning, MATLAB, Python, Data Science

  • Research Intern

    2013 - 2013
    TRIUMF
    • Participated in a research internship at TRIUMF on the IRIS experiment with Dr. Rituparna Kanungo.
    • Improved detector calibration with elastic scattering simulations in C++. The goal of the experiment was to demonstrate the particular halo structure of the lithium 11 isotope.
    Technologies: Linux, C++, Data Science

Experience

  • Learning Generated Abstractions

    When we program an AI to learn simple yet purely virtual representations, what happens in the middle of the process? I used GANs to generate abstract images from samples obtained via simple procedures in Python.

  • Reliable Vision System for Wildlife

    The goal of this project was to build an autonomous camera system that automatically detects and counts bird species based on input images. We used YOLO v3 and Inception ResNet v2 algorithms for bird detection and classification, respectively.

  • Installation with Ed Fornieles Studios

    I powered a Unity art installation with real-time financial analytics API in Node.js on AWS during La Biennale di Venezia 2019.

Skills

  • Languages

    Python, C#, JavaScript, SQL, C++

  • Libraries/APIs

    Scikit-learn, NumPy, Pandas, TensorFlow, Keras, Matplotlib, Vue, Theano, React, Flask-RESTful

  • Paradigms

    Data Science, Test-driven Development (TDD), Object-oriented Programming (OOP), Testing

  • Frameworks

    .NET, Express.js, Flask, CODE, JSON Web Tokens (JWT)

  • Tools

    Git, Sublime Text, MATLAB, Visual Studio, ReSharper, Jira, BigQuery, Apache Airflow, Celery

  • Platforms

    Linux, Windows, Amazon EC2, MacOS, Visual Studio Code (VS Code), Jupyter Notebook, Docker, Salesforce

  • Storage

    Google Cloud, MongoDB, MySQL, PostgreSQL, SQLite, Memcached, Amazon S3 (AWS S3)

  • Other

    Deep Learning, GitKraken, APIs

Education

  • Master of Science Degree in Data Science and Operations Research
    2015 - 2018
    HEC Montréal - Montreal, Quebec, Canada
  • Bachelor of Science Degree in Theoretical Physics
    2011 - 2014
    Université Laval - Québec, Canada

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