Education & Skills
This page highlights academic degrees, continuing education, and selected professional course completions. Click any image to open it full size.
Degrees & Credentials
A selection of formal degrees, diplomas, and professional learning milestones.
Education
My academic foundation combines engineering, computer science, data science, machine learning, and economics. I earned a Bachelor of Engineering in Chemical Engineering from McGill University and later completed a Bachelor of Computer Science with Distinction at Concordia University, including a Minor in Economics. I later earned a Diploma in Data Science, which provided statistical training as well as machine learning skills. This well-rounded combination reflects a grounded background in analytical thinking, technical problem-solving, and interdisciplinary study.
Skills
- Data science, statistics, analytics, visualization, and insight extraction
- Machine learning, supervised and unsupervised learning, regression, clustering, and classification models, pipeline creation
- Extensive LLM experience, prompt engineering, skilled multi-agent workflow design, n8n, RAG implementation, MCP tooling, and skill.md file creation and maintenance
- Programming in Python, C++, C#, and JavaScript
- Business analysis methodology and toolset founded on BABOK and TOGAF-based enterprise architecture knowledge
- Project management, product management, product ownership (CSPO), Agile, Scaled Agile training with experience
- Requirements elicitation, data-driven requirements analysis, prioritization, and MVP delivery
- Attuned communication skills at all levels of an organization
- Sales, advertising, and marketing experience
- Fluent in English, French, Hindi, and Creole
Curriculum Vitae
A focused summary of experience drawn from the CV, with emphasis on data management, governance, compliance, and AI-driven delivery.
Most recent and relevant experiences include leading product, business analysis, and process design work in environments where data governance, retention, privacy, classification, reporting, and compliance were central to delivery. This includes collaboration with product, architecture, security, legal, and engineering teams to support GDPR, PCI, SOC 2, HIPAA, audit readiness, and regulatory reporting practices. More recently, this has extended into AI-focused business process automation using n8n-based multi-agent workflow design, including MCP-tooled and RAG-grounded solutions built to streamline operations, control outcomes, and reduce manual effort.