About

Andrew Paul Acosta is an experienced data analyst with a deep knowledge of finance and statistics, statistical analysis, and enterprise risk analysis. He is currently working as a Data Scientist at Milesius Capital Resources LLC and has over 5 years of relevant experience in the field. Andrew has expertise in power market risk model analytics of PJM and other ISO/RTO markets, including peak/off-peak load analysis, using day-ahead and real-time market data of power generation, transmission, and congestion at various LMP zones/hubs. He has also worked on big data predictive analysis projects, including relational data mining, neural network, nearest k-neighbor, association rules, time series, regression trees, sequence clustering, and Naïve Bayes. As a mentor and accomplished practitioner, Andrew has extensive experience in market risk measurement, volatility, predictive modeling, option pricing, risk analytics, yield curve modeling, analysis of financial market data in researching fixed income instruments and derivatives, especially mortgage products. He is also skilled in exchange-traded derivatives, margining, and strategy. Andrew has experience in analyzing cashflow-based valuation models and the ability to analyze/estimate sensitivity of model parameters to pricing. He has worked with Monte Carlo simulation, Hull-White, Black-Karasinski, AD&Co, AFT, Bloomberg, Intex, and SPAN margin. Andrew's specialties include data mining/KDD, knowledge management, financial derivatives and their markets, energy/power markets, coding (Python, R, SQL, C++, Java, MATLAB, VB), futures, options, swaps, FX, risk management, pricing models, and hedging strategies. He is an Association for Computing Machinery (ACM) Senior Member. Andrew is a highly skilled and knowledgeable data scientist with expertise in finance and statistics. He is a valuable asset to any organization looking to improve their risk analysis and predictive modeling capabilities. Andrew can be contacted at <andrew@acm.org>.