Requires a PhD in Math, Statistics, or a related quantitative field plus 3 years of professional quantitative finance or financial engineering experience, in one or multiple asset classes. Employer will also accept a Masters degree in Math, Statistics, or a related quantitative field plus 5 years of professional quantitative finance or financial engineering experience, in one or multiple asset classes. Must include 3 years of experience with each of the following 1 programming in Python, R, Java, Scala, and SQL; 2 financial market data and taxonomy; 3 processing big data on distributed architectures, including Spark and Hadoop; 4 machine learning tools including ScikitLearn, PyTorch, and TensorFlow; 5 NumPy, Pandas, statsmodels, and matplotlib; 6 statistical model building and validation, inferential statistics, and econometrics; 7 quantitative asset pricing and risk management in either a sell or buy side firm; 8 risk measures including Greeks and valueatrisk, risk attribution, and factor models; and 9 Bloomberg terminal and data APIs.
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