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Major Concepts

Data Scientist

A data scientist is a multi-disciplinary person who uses math, programming/technology, domain expertise to give competitive edge to a business. The demand for data scientists has grown significantly in recent years as there is a large amount of data that can be analyzed to improve a company or business. 


A data scientist is difficult to find as the role requires a multiple skillset. The responsibilities include collecting and exploring the data to find meaningful patterns and apply different modelling techniques to solve a particular business problem. The data scientist must be able to communicate his ideas and observations from the data to clients or business stakeholders and help them in business decisions.





Mathematics and Statistics



  • Math is one of the key discipline of all sciences, the same goes for data science as well

  • Basic matrix algebra, probability and statistics play a major role in data science


Technology



  • Data Science techniques can be implemented using different technologies. Python and R are the 2 most widely used programming languages for data science

  • Tensorflow, keras and pytorch are the major libraries used for deep learning


Business



  • Domain expertise or business knowledge is a key factor that allows one to get an idea of how data science knowledge can be used to solve specific business problems

  • Even before starting a data science project, business expertise can be used to formulate a problem statement which is helpful to lead the project in the right direction




The 4Ms of Data Scientist Skill Training



The success of a data scientist does not depend just on gaining expertise at programming languages like python or R, but understanding the data available and how to use it to meet the business targets by building the appropriate model increases  the value of a data scientist. The data scientist should be able to communicate with the team and also with the domain experts if necessary.


Job Market for Data Scientists



  • According to industry estimates, organizations in the USA alone face a shortage of 140,000 to 190,000 employees with deep analytical skills. US also requires 1.5 million managers and analysts who can analyze big data and make decisions based on the findings.

  • When the consulting firm accenture surveyed its clients on their big data strategies, more than 90 percent said they planned to hire more employees with expertise in data science - most within a year. However, 41 percent of the more than 1000 respondents cited a lack of talent as a chief obstacle.

  • As per a survey conducted by Analytics India Mag and Great Learning, around 97000 analytics, data science jobs are vacant due to a lack of qualified talent.







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