KARL J GOMINDES

Economics graduate with experience in business analysis, financial modeling, and data-driven decision-making through internships and competitive case-based projects. Skilled in Excel, SQL, and Tableau, with a strong foundation in market research, stakeholder communication, and cross-functional collaboration. Eager to bring analytical thinking and structured problem-solving to roles in business analysis, financial services, and strategy-focused environments.

Advanced Analytical and Econometric Research Experience

• Designed and implemented econometric models across six original research projects using real-world datasets and regression techniques including logistic, linear, and interaction-term-based OLS.
• Achieved 96% directional forecast accuracy in commodity pricing models (gold and oil), integrating central bank policy analysis, geopolitical forecasting, and sentiment indicators, drawing on Bloomberg and Financial Times data.
• Led a Monte Carlo simulation project forecasting Canada's public debt-to-GDP ratio under 300 randomized scenarios, building fan charts and performing sustainability analysis under IMF and PBO criteria.
• Co-authored a sports econometrics paper analyzing 12,000+ European football matches to measure crowd-driven shifts in home field advantage pre- and post-COVID, using logistic regression in R to isolate behavioral effects (e.g., social facilitation, marginal externalities).
• Investigated wage inequality in Canadian labor markets using the Mincer model; demonstrated gender-specific returns to education with interaction terms, and presented policy recommendations for addressing structural wage gaps.
• Conducted price forecasting and sensitivity analysis for LVMH's Neverfull bag using macroeconomic indicators (GDP, inflation), scenario modeling, and elasticity-based pricing theory to determine strategic pricing outcomes for luxury goods.