Skills:
Statistics: Regressions, MSE Estimator, and Monte Carol Simulation - Utilizes statistical methodology to analyze energy price characteristics, develop and assess hedging strategies. Mathematics Algorithms: Machine Learning (Neural Networks, Logistics Regression, Support Vector Machine), Optimization (Dynamic Programming, Gradient Methods, Lagrange Multiplier algorithms, Duality and Convex Programming) - Research Mathematics Optimization Algorithms applied by U.S. wholesale electricity market operators (ISO), with results presented in prestigious publications and conferences. Develop an electricity load forecasting method using Machine Learning and Data Analysis techniques. Quantitative Finance: Value-at-risk, Cash-Flow at risk, Collateral, Correlation, Volatility, Option Pricing and Greeks (Sensitivities), NPV, DCF, IRR Modeling: Build various risk and valuation models for different energy commodity portfolios. Computer Programming: Build in-house market analysis tools employing C, Matlab, VBA, SQL, Java, Python, and Powerworld.