• Conducted forecasting and pricing on over 300 military equipments based on tech stack, criticality, support coverage, and testing coverage, with various pricing models on NATO contracts valued over $40 billion CAD.

• Built simulation-based, GPU-accelerated ML algorithm pipelines using Airflow, ML Engine, BigQuery, and Google Cloud Storage, used for training and evaluation of both production and offline forecasting algorithms. Built the reference team’s data infrastructure using SQL, creating processed logs, aggregate tables, and reporting tools

• Deployed Random Forest Classifier NLP model with Scikit-Learn, NLTK, and Pandas on GCP Vertex AI to categorize defence spending with 90%+ accuracy, improving content and product.

• Increased sales and services conversions by over 20% by conducting user research, A/B feature testing, and market analysis to facilitate improved push notification campaign targeting strategy in Microsoft Power Automate.

• Boosted user engagement and digital service quality by developing a Python chatbot in 3 weeks and leveraging Tableau, Plotly, and Python for data visualizations.

• Built reporting tools using Power BI and SQL, providing data access to a team of 40 limited-access vendors.

• Worked remotely in an agile, communicative, and self-directed manner as part of a collaborative, interdisciplinary, diverse, and geographically-dispersed team. Organized, directed and tracked team progress as scrum leader for infrastructure data pipelines, driving daily standups, biweekly syncs, demos and retrospectives