Analytical reports combining R, Python, and large-scale datasets to deliver complex, detailed insights into concise briefing notes and reporting. Designed to answer executive questions, profile industries, and surface evidence-based insights from data across multiple sectors.
Owned and delivered Hiring Demand Bulletin, providing a comprehensive view of labour demand across regions and industries. Synthesized large-scale labour market data into concise, executive-ready insights for stakeholders.
View Report →Automated data pulling and report generation for 18 industry profiles, processing 2M+ rows of data. Built a scalable data pipeline that reduced reporting time from approximately one month to a single execution — a 95%+ efficiency gain — while improving consistency and reliability.
Watch Demo →Designed a forward-looking economic analysis assessing how Canadian crude prices respond to net-zero transition scenarios and U.S. policy shifts. Combined API-sourced data, scenario modelling, and advanced visualization to translate complex market dynamics into decision-ready insights for stakeholders evaluating risk, pricing volatility, and long-term competitiveness.
View Project →Developed a data-driven analysis integrating large-scale energy datasets to quantify how pipeline constraints impact crude shipments and provincial royalty revenues. Built an end-to-end analytical workflow in R, combining API-based data pulls with structured transformations and state-of-the-art visualizations to surface bottlenecks and revenue sensitivities in Canada's energy system.
View Project →Constructed a comprehensive analytical framework to evaluate Canada's evolving electricity mix, linking generation sources to emissions outcomes under changing demand conditions. Leveraged large datasets and automated pipelines to produce high-impact visualizations and an R Markdown report, enabling clear interpretation of decarbonization trade-offs for energy policy and market analysis.
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