Data is said to be the oil of the 21st century especially in a digital economy, data, like oil, is more valuable than ever. With this growing presence of data people realised and introduced new ways of using it to learn important details about their consumers, employees.
We can see the use of data in every facet of our lives even if we don’t realise it. From Google Search, to our next youtube recommendation, from our next purchase to our weather predictions every organization existing on the internet is using the ever prevalent and copious amounts of data to improve and better understand models of their business better.
Ongoing Application Forms - 2020
And for utilizing this raw and untrained data, there is a huge need for skilled, trained and experienced data scientists.
Subscribe to Get Updated Information about How to Start a Career in Data Science in India – UG and PG Courses - Admissions
A data scientist is someone who takes huge amounts of data and then uses various statistical and analytical methods to predict and analyse progress, make decisions and build solutions.
The conclusions data scientists and analysts come up with can be used to provide businesses and agencies with important insights.
As it turns out there is a huge shortage of these skilled professionals in the market and as more and more businesses and organisations realise the huge potential manoeuvring data brings to them this demand is only to tip in favour of data scientists and analysts.
Data Science profile is all about playing with an enormous amount of data and gaining meaningful insights for decision-making in an organisation.
In order to become a skilled data scientist, one must have expertise in a plethora of fields such as BI tools, cloud solutions, visualisation tools, programming languages, data management tools among others.
There are a number of job roles in data science which are currently available among organisations such as machine learning expert, data architect, quantitative analysts, big data expert, data visualisation experts hence people interested in this field must be clear on what area of data they would like to go in.
Scope for data science in India
There is huge scope for data science in India. It is prevalent in different sectors such as banking, healthcare, biotechnology, e-commerce, energy and automotive industry, pharmaceuticals and telecommunications.
The median salary for a data scientist in India is around 6 lakh rupees per annum. However, this varies with the years of experience, qualifications and skill level you have. Senior data science professionals with more than 10 years of experience earn more than 20 lakhs per annum.
Becoming a data scientist entails technical as well as non-technical skills. Some of the skills required are
A person interested in data science usually goes for a masters or PhD in either statistics, analysis or computer science. There are many programs available in India as well as in other countries that provide a proper education for a data science career. Such programmes are really popular these days with almost every major university providing a data science career path. Besides enrolling in a program, a data scientist must also excel in a programming language to clean and structure the data as well as have good analytical knowledge to interpret the data.
Unless you can communicate your data analysis to other members of your business the findings remain useless. Besides the more important technical skills, having non-technical skills such as having in-depth awareness of the business and good communication skills are very important for success in this field.
Data Science in India
Data science is a fairly new term to the Indian education system, but interested candidates can choose highly mathematical fields such as ‘Statistics’ as their majors for their undergrad. Statistics is offered as the main field of study in BSc Statistics in many colleges in India such as DU, Xaviers, ISI and more.
There are many post graduate programs being offered in data science in India nowadays besides the Masters route. A student can take any of these routes to further their education, especially since most jobs require a post graduation in this field. Most programmes are spread over a year or two and after completing these courses are considered a strong and competent Data Scientist. Some of the universities which also offer a masters in data science or its many sub domains include Symbiosis, IITs, IIITs, ISEs and many more.
The journey will complete when you start focusing on the practical applications of the topics which you have been learning. This involves doing as many as open source projects such as from Kaggle, making your own fun side projects on Github and being an active part of the open source Data Science community. Doing internships in Data Science companies is a also great way to gain more experience with real-time projects as the job market is tilted more in favour of experienced data scientists.