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The term ‘Data Scientist’ was actually coined in 2008 by D.J Patil and Jeff Hammerbacher, who back then were leaders of data and analytics efforts at LinkedIn and Facebook, respectively.  As they were doing a lot of large-scale data analysis and data product development work that went beyond the traditional role of data analysts or business analysts, they coined the term ‘Data Scientist’ and crowned themselves with this new designation.
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According to Wikipedia, a Quant or Quantitative analyst in the financial world is a person who specializes in the application of mathematical and statistical methods – such as numerical or quantitative techniques – to financial and risk management problems.
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Data science is the most interesting field which makes use of scientific processes, methods, systems, and algorithms for obtaining insights and knowledge from various structured and unstructured data.
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In this post, we will review the basic tools that every quant developer should have in their toolbox. To do so, we will create a small project to modify a free software library and publish our changes.
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