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Group Description
The Quantitative Investing Group brings together professionals seeking to incorporate cutting edge quantitative investment techniques and alternative data sets in their investing and risk processes. Members include (but are not limited to) discretionary and systematic portfolio managers, risk managers, traders and fundamental analysts, data strategists, quantitative researchers, and others. The topic covered range from quantitative alpha generation, big data as well as alternative datasets, quantamental signals i.e. the intersection of fundamental analysis and quantitative decision making, mathematical and statistical aspects of modern quantitative analysis, use of programming languages or quant tools, Natural Language Processing, machine learning for investing and risk management, theory and implementation of AI in finance and more.
Guest Speaker
Nicole Koenigstein, Data Science and Technology Lead, impactvise, Quantitative Research Consultant, quantmate
Nicole Koenigstein is a Data Scientist & Quantitative Researcher currently working as Data Science and Technology Lead at impactvise, an ESG analytics company, and Technology and Quantitative Research Consultant at quantmate, an innovative FinTech startup that leverages alternative data as part of its predictive modeling strategy. She is the author of Mathematics for Machine Learning with NLP and Python.