Data Science is a field where scientific methods, processes and systems are used to extract knowledge or insights from data in various forms. Data Scientist has become a profession of high demand in the recent years, with organisations offering insane packages to lure the best ones in the industry. It has been titled as “The Sexiest Job in the 21st Century” by Harvard Business Review in October 2012. A study by McKinsey suggests there will be more than 490,000 jobs in data science by 2018 as compared to the number of Data Scientists (200,000 approx.) available. Globally, there will be twice the amount of demand as compared to the supply by 2018.
The above data proves the growing demand for data scientists in every organisation across different industries. According to NASSCOM, the job market will see a surge in the job openings for Analytics professionals from around 90,000 at present to around 3,00,000 in 2018; which will definitely open doors of opportunities for Data Scientists. Data Scientists are among the professionals having the highest job satisfaction across industries as mentioned in a Data Science report by CrowdFlower in 2016.
It’s good to know all about this growing demand for data scientists. However, do you have the skills and the knowledge of tools that are commonly used in data science? Here are some of the common skills that a data scientist should have:
- Data Scientists are expected to have high-level of analytical skills. That is why a large percentage of the expert Data Scientists is from Mathematics, Statistics or Engineering background. Most of them hold a Master’s Degree or even a PhD. That is why, if you are from a Science background, it would help a lot.
SAS is a software suite for information management, advanced analytics and reporting. It is used by more than 60,000 companies in over 135 countries and is a market leader in analytics. It is the commonly used software in the Indian analytics market despite its price monopoly.
A statistical computing software developed by Mathworks, MATLAB has a wide range of add-ons and functionalities that help in various data analysis. It allows matrix manipulations, plotting of functions and data, implementation of algorithms and creation of user interfaces.
R is an open-source programming language and software environment for statistical computing and graphics. It is widely used by statisticians and data miners. Its popularity has increased over the years according to O’Reilly Survey in 2014 it was the most-used data science language after SQL and is one of the highest-paid IT skills. Data scientist in many big companies like Facebook and Google are already using R.
Python is one of the most commonly used programming languages used in data science roles. According to KDNuggets, it is the second-most in-demand skill in the job market after SQL. It is also the official language of Google; the Google App Engine was originally built on Python. Other big companies which use Python are Quora and IBM.
It is the most in-demand skill and also, one of the most powerful tools for many expert data scientists. SQL is a database management language for relational databases. SQL along with R and Python forms the triumvirate of programming languages, which any data scientist worth his/her salt is expected to be proficient in.
Not a necessity for being an efficient Data Scientist but with the growing popularity of Hadoop in processing Big Data, it is a skill worth having. It is a Java-based programming framework used to process large data in a distributed computing environment.
Also Read>>Top Reasons to Learn Python and Hadoop
You have got the ability to analyse the data of the organisation. This data is going to be highly important in growing the business and if you understand the business problems of the company, you can help the company by leveraging this data to provide useful solutions.
Soft skills are always important when you are working in an organisation. You will be in regular touch with the sales, marketing and other non-technical teams. Your data findings can be useful only when it can be translated into proper business opportunities. You must be able to communicate your findings in a manner that other non-technical people can understand.
If you feel like you are lacking in some of the areas, there are always a way to get the required skills. There are various online courses on these topics and get the skills that you need to start your dream career in Data Science.
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