Julien St-Pierre Fortin
Verified Expert in Engineering
Machine Learning Developer
Julien's expertise is deploying software solutions in data and AI. 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 projects.
Slack, GitHub, Google Docs, Miro, Figma
The most amazing...
...product I've built is Succession HQ, a SaaS app to optimize operations for manufacturing SMBs.
- Built retrieval-augmented generation algorithms to power the product's business insights engine.
- Architected and built the data infrastructure, as well as the app's back end and front end collaborating with the engineering team.
- Worked with the CEO to define business requirements and processes to reach our goals.
- Collaborated with the design lead to build our design system.
- Played a role in developing Coveo's latest generative question-answering capabilities.
- Unified data modeling for the service and support line of business.
- Improved data access security of search engine data.
- 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.
- Constructed machine learning models using scikit-learn and TensorFlow based on user behavior to predict cohorts' lifetime value (LTV) and profitability.
- 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 a Vue-based user interface to visualize model predictions.
- Developed deep learning models with MATLAB to predict water temperature from meteorological data to support engineering at the 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.
- 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.
- Collaborated with an international team of physicists.
Learning Generated Abstractionshttps://julienstpierrefortin.com/posts/learning-abstractions/
Reliable Vision System for Wildlife
Installation with Ed Fornieles Studioshttps://capesaro.visitmuve.it/en/mostre-en/archivio-mostre-en/breathless-london-art-now/2019/10/20942/breathless/
Python, C#, SQL, Snowflake, Java, TypeScript, C++, Scala
Scikit-learn, NumPy, Pandas, TensorFlow, Matplotlib, PyTorch, React, Keras, Node.js
Git, AWS CLI, Terraform, MATLAB, BigQuery, Apache Airflow, Slack, GitHub, Google Docs, Figma
Data Science, Test-driven Development (TDD), Object-oriented Programming (OOP)
Jupyter Notebook, Docker
Deep Learning, Artificial Intelligence (AI), Machine Learning, Modeling, Physics, OpenAI GPT-3 API, Numerical Methods, Data Build Tool (dbt), OpenAI GPT-4 API, Generative Adversarial Networks (GANs), Miro
.NET, Next.js, Unity
Master of Science Degree in Data Science and Operations Research
HEC Montréal - Montreal, Quebec, Canada
Bachelor of Science Degree in Theoretical Physics
Université Laval - Québec, Canada
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