Jyoti Nigania

Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree. ...

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Hi,i am writing blogs for our platform House of Bots on Artificial Intelligence, Machine Learning, Chatbots, Automation etc after completing my MBA degree.

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Data Science Is The Role That Is Giving Many More Opportunities In Professional World

By Jyoti Nigania |Email | Feb 19, 2019 | 5898 Views

Data science is giving too many opportunities today in the professional world. As the number of business concerns using data analytics is on the rise, so is the number of jobs in this field. Last year the analytics industry recruited more than 16,000 fresher candidates and this will increase in the upcoming years.
Data science deals with enormous amounts of raw data. Data scientists wrangle the given data and find meaningful insights from it. These insights are used to taking strategic decisions.

Who is Data Scientist?
Data scientists are those professionals who turn masses of unstructured data into analyzable results. They find patterns and trends which are hidden in them. They usually use various software specially organized for this task and find inferences which can be easily explained to people in the organization who does not belong to the IT realm. They usually indulge in experimentation and research to find new technological solutions for the analytics process. They come up with various models and algorithms which in turn help business concerns to face the new daily challenges.

Role of Data Scientist:
As a data scientist, one may have to take part in various activities that are involved in the entire procedure of data science. Just because data science has many areas to focus on like data collection, mining, cleaning, visualizing, interpreting thus one can say that data scientists too can have many roles like of data engineer, architect, programmer etc.

Some of the responsibilities of this profession are:
  • Ask questions related to the industry trend and conduct research.
  • Extract and obtain data from various sources like web, databases, media, cloud etc.
  • Clean the data from any kind of anomalies and gaps that may become a hindrance in analyzing.
  • Explore the data thoroughly to find all the hidden patterns and trends which can help to make the data more understandable.
  • Use various statistical tools and machine learning to prepare the data for analytical use in real-world problems.
  • Devise and design algorithms which will use the data patterns as their requisite.
  • Communicate and present the data inferences to the management which can help in taking a decision.

How to become a Data Scientist?
To become a data scientist one need to have mathematical, statistics, programming and communication skills. On top of that, a person should have the curiosity to ask market relevant questions and should have inquisitiveness to search and find data from all directions possible.
Apart from all this, a data scientist must have skills relevant in using tools and techniques of analytics. Some of them are:
  • Mathematics- linear algebra and calculus.
  • Statistics- statistical models, probability and hypothesis techniques.
  • Database management- SQL and NoSQL
  • Data mining and cleaning
  • Data visualization tools- d3.js etc
  • Reporting techniques
  • Python, R, SAS and their libraries.
  • Java, C/C++
  • Hadoop, Apache Spark, and Flink
  • Industry knowledge
  • Communication skills
  • Analytical problem solving and decision making

Need for data scientists is in many sectors like telecommunications, E-commerce, finance and banking, agriculture, research and development, insurance, retail, manufacturing and many more.
If you have a computer and mathematics background, then boot camps and certifications can be of great help in becoming a data scientist. Proper guidance from Data science certification can help you in choosing the required training needed for the industry of analytics you are interested in and help grab the opportunities.

Source: HOB
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