Experience
2025 — Now
2020 — Now
2020 — Now
> Designed and built end-to-end ETL machine learning pipeline from ingestion output
> Setup Kubernetes and Argo Workflow on local server to handle container orchestrating and job dispatching
> Optimized process build times to maximize CPU efficiency using all 20 threads
> Minimized training time while maintaining model performance by tuning hyperparameters
> Designed custom model architectures in Tensorflow and custom loss functions in Numpy to increase model performance
> Built backend for efficient asyncronous job processing using a DAG
> Used Data Science principles to design features leading to increased model performance
Machine Learning Pipelines:
> Data Modeling | Data Architecture | Database Architecture | Timeseries Forecasting
> Optimize Performance | Parallel Processing
> Hyperparameter Tuning | Preprocessing | Custom Loss Function | Feature Engineering
> Scikit-learn | SciPy | TensorFlow | Keras | PyTorch | CUDA | GPU vs CPU
Design and Build ETL pipeline:
> Data Modeling | Data Architecture | ML | AI
Development Tools:
>Python | PySpark | Spark | Jupyter Notebooks | Containerized Development
Data Ingestion:
> API | REST / RESTful | asyncronous client-server data streaming
Scalable Data Processing Solutions:
> Docker products | Kubernetes | Argo Workflow | Apache Airflow | Luigi | Container Orchestrator
Database Technologies:
> CSV | JSON | Relational Database
Self-motivated personal project I have been consistently working on, 10-30 hours/week.
2023 — 2025
2023 — 2025
Montreal, Quebec, Canada
> Build and maintain highly reliable computed tables, incorporating data from various sources, including unstructured and highly sensitive data
> Access, manipulate, and integrate external datasets with internal data
> Building analytical and statistical models to identify patterns, anomalies, and root causes
> Leverage SQL and Python to shape and aggregate data
• Support and maintain the primary production pipeline, ensuring accurate and on-time delivery of data for data consumers
• Business owner for a dev team (6) to ensure Continuous Improvement Continuous Deployment (CI/CD) - - Reporting process of ongoing enhancement, deployment, and monitoring of pipeline health through key metrics
• Oversaw transition into production for our cloud based data service "Skywise"
• Assessing the impact of upstream changes allowing prioritization and proper communication to customers
• Headed data governance initiative to lead new program and to provide algorithms to internal clients
2022 — 2023
2022 — 2023
Montreal, Quebec, Canada
• Developed a solution to enhance visibility into pipeline throughput, resulting in faster identification of various issues
• Investigated two algorithms designed to forecast system failures in advance of scheduled maintenance intervals
• Monitoring and improving data pipeline (ingestion to delivery) to meet KPI’s
2022 — 2022
2022 — 2022
Montreal, Quebec, Canada
Programming:
> C++ | OOP | Debugging
> Used system knowledge to solve issues in production
> Worked with system engineers to support with domain specific knowledge
> Supported real-time programing in time critical applications
> Memory Management
Education
The University of Texas at Austin
Masters of Science
2023
Carleton University
Bachelor's degree
2016 — 2021
International School of Luxembourg
International Baccalaureate
2013 — 2016