Eric is a Senior Data Scientist at SGX Analytics, in charge of developing and coding custom made algorithms for a wide range of data science problems. Eric has several years of experience in the capital markets with emphasis in research and data science. Before SGX Analytics, he was a Data Scientist for Ttwick Inc, in charge of developing time-series analyses of many proprietary data sets, as well as customized computational linguistic algorithms to transform unstructured into structured data. Prior to Ttwick, Eric was a Teaching Assistant at NYU, where he taught Cross-Sectional and Time-Series Econometrics, and performed distributed Monte-Carlo simulations on NYU’s high performance cluster machines. Prior to NYU, Eric worked for the Federal Reserve Bank of Boston, performing econometric analysis and macroeconomic forecasting. Eric has a PhD in Economics with concentrations in Macroeconomics, International Economics, Econometrics, and Computational Economics from NYU, and a Majors in Economics and History from UC San Diego, where he graduated Summa Cum Laude. He codes in Python, SciPy, NumPy, Scikit-Learn, Pandas, R, Matlab, Fortran 90, C++, Java, Mathematica, Theano and TensorFlow. Eric was recently a featured speaker at Bloomberg NY in the topic “Data Investing: Using Python and Machine Learning to gain insights into the dynamics of stock price returns around earnings announcements”.