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

Verified Expert  in Engineering

Software Developer

Location
Montreal, QC, Canada
Toptal 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.

NumPyPythonPandasTensorFlowKerasWindowsLinuxGitSQLFlaskAmazon EC2.NETC#Express.jsTest-driven Development (TDD)

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

Python - 7 yearsMatplotlib - 6 yearsScikit-learn - 4 yearsTensorFlow - 4 yearsPandas - 4 yearsJavaScript - 4 yearsGit - 4 yearsSQL - 3 years

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.

Work Experience

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

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.

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

2015 - 2018

Master of Science Degree in Data Science and Operations Research

HEC Montréal - Montreal, Quebec, Canada

2011 - 2014

Bachelor of Science Degree in Theoretical Physics

Université Laval - Québec, Canada