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In simple words and or in a sentence it can be defined that a data scientists job is to analyse data and give valuable and actionable insights.
Of course if it would be this simple then Harvard would not call it ‘The sexiest job of the 21st century’ so clearly the data scientist job comes with some prerequisites, certain qualification and skills along with experience. The role cannot be easily defined, there is no standard set of skills and experience which can be defined, and even if we go to an extent and make an exhaustive list, the skill sets will be nearly impossible to find in one person.  There are many nomenclatures that are attached to the wider role, like data engineers, data analyst, data mining specialist etc.., which further confuses organisations and even individuals who wish to pursue a career in data science.
So a data scientist could draw upon a few common disciplines, it is important to note that a data scientists level of experience and knowledge in each domain varies in degrees, starting from beginner, to proficient and expert.
Some common disciplines include, knowledge in math, statistics, advanced computing knowledge, visualisation techniques, to have a hacker’s mind set would be an advantage, essential and relevant domain expertise, and lastly a data scientist has to be excellent in data engineering and also be skilled in scientific methods of data processing.
You can become a data scientist with mostly the common educational and work experience background. However, your effectiveness and efficiency can be determined by how good you are in the four fundamental areas.

  • Business Domain
  • Statistics and probability
  • Computer science and software programming
  • Written and verbal communication

Consider these as the four pillars for a good data scientist. Based on these four pillars, a data scientist will be able to leverage existing data sources and create new ones in order to extract meaningful information and actionable insights. With the help of these insights businesses can take decisions intended to increase revenue.

Data Scientist do…

  • The identification of data analytics problem which in turn offers great opportunities to the business
  • The determination of the correct data sets and variables to look into
  • Collection of structured and unstructured data sets from all possible sources
  • Separation of unstructured data, validating it to ensure accuracy and completeness
  • Using algorithms to mine targeted data
  • Analysing the information and identify patterns and trends with an inquisitive mind Exploratory data analysis
  • Interpreting the data to see factual finding, creating hypothesis and trends, proving it with findings
  • Communicating in clear language with the leadership team so that everyone can understand the implications easily.

Harvard is right when it says that data scientist is a highly important and demanding role that can have a huge impact on business, in many ways, financial, operational, strategic and so on.
Companies collect a lot of data in recent times, this data is usually neglected or underutilized. There is a lot of insight one could get from this data if it is extracted for actionable information it can optimize customer success, and subsequent acquisition, retention and growth. A data scientist is the person who can make this possible.

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