What is the scope for data science in 2020? Applications and Salary
This Article has been Published First On: https://www.crampete.com/blogs/scope-for-data-science-in-india/
Intro
A mixture of many fields of science that deals in formulas, patterns, statistics, math and business give birth to one of the most demanding subjects known as data science.
Data science draws inspiration and its basis mainly from the fields of statistics and business intelligence and combines computer science and other modern technologies like artificial intelligence and machine learning to make smarter decisions.
The data is analysed and the results of the analysis are used to draw conclusions and make decisions based on the supporting data.
As such,a data scientist has a lot to offer the world of industries. In this blog, we are going to see what the data scientists do and what is the scope of data science in India and the world.
//Quote “Each pattern describes a problem which occurs over and over again in our environment, and then describes the core of the solution to that problem, in such a way that you can use this solution a million times over, without ever doing it the same way twice.”
- C. Alexander
Responsibly of the data scientist.
- Collect the huge amount of data available on the internet through the company site as well as third-party sources like surveys and social media.
- Clean up the irrelevant data and store the data in a database.
- Research the data and frame questions which need to be answered.
- Use modelling, statistics and analytics programs to organize the data into a predictive model.
- Analyze the data and come up with trends and opportunities and answers for issues or problems when required.
- Write up new algorithms to solve issues if nothing existing works. This also means that data scientists have to build data science tools if need be.
- Recommending changes to existing system and strategies.
- Presenting the analyzed results, trends, opportunities and even weaknesses in an understandable manner across various teams with the help of visualization techniques.
What you should do to be a data scientist?
There are multiple paths one can take to be a data scientist. The longest route is to start with a different role, a data analyst and then work up from there based on your experience. The faster and easier way is to become a data analyst and then upskill with whatever is necessary to become a data scientist. Say, for example, that you need to work with a set of tools that are written in python.
Then the first step is to take an online course on Python and gain working knowledge of it. Similar study any other programming language language that has a strong presence and use for data science.
Another route, the most expensive one, is to study Masters degree in data science at a reputed institute. This is not a foolproof method and you have shell out huge amounts of money for the degree.
The more affordable route and the best is to choose a certification course in data science. Crampete offers an online course on data science wherein you get a lot of practice time and get to do hands on projects. We also offer classes offline -data science course at our centre for learning.
General benefits of Data science
Smart decisions
In this day and age, data-driven decisions are considered as smart decisions. And data science plays an important role in not just helping make decisions that are smarter, but also helps them do it faster. Every decision is reviewed again after some time and the results are evaluated.
This way, data scientists give an approach to evaluate and improve the company’s overall performance.
Target identification
Target identification has never been easier. Every product and service needs to target the right demographics to make the maximum benefit or sales of their product or services.
As such, using analytics and available data sourced from a variety of channels, it becomes easy to identify and further refine the set of the target audience for the service or product. With this, companies can tailor their services for demographics and can increase their profitability.
Transforming risk analysis
Data available is humongous and analyzing this data along with predictive analysis allows us to be forewarned of certain risk scenario.
We can then propose a plan of action to mitigate the risk and suggest alternative workings to achieve our goals. All this is possible only with data science tools which help us analyze huge amounts of data faster and gain actionable intelligence from it.
Average Salary earned by a data scientist in India.
The salary of a data scientist averages at Rs.7,00,000/- per annum in India. Of course, you can get a better salary by improving your skills, and resume.
The salary is based on many variable factors like the industry of employment, the job profile, the education, the location of the job and experience. If you have pluses on these boxes, you can get a better salary by negotiating for your worth with the recruiter.
Scope of Data Science in India
India is no stranger to progress in science and technology. We are trending in IT and healthcare and have a strong presence across a multitude of industries. These industries have a dependence on data science to make smarter decisions that are based on the data that indicate consumer preferences and help market it to the right group of people. This means that there is no limit to the scope of data science in India.
The only restriction is the extent of this dependency on data science across various industries. Every industry has something to offer to the customer and data scientists find a way to help them do this efficiently and at a higher profit(That at least is the hope). Let’s see some of the industries and what data science does for them.
Scope of Data science across industries.
The influence of data science is enormous in multiple sectors. Every below-mentioned industry has a high dependence on data science and offers great opportunities for a data scientist.
Recruiting
A recruiter has to go through any large number of resumes at any given time, especially more so in the recruiting season. One of the biggest challenges for the recruiter is to find the right recruit based on the resumes and that is like finding the right needle in the needle stack. But this difficult job of epic proportions is made very easy with the advent of data science.
Data scientists use the data from every avenue open to them, including social media and recruiting websites to find the right candidate for the position. By data mining and processing of resumes, any company can help their recruiter to find candidates faster as well as accurate. Know how to write a great resume so that your resume will be selected even stringent filters are applied with data science. This will help you get recruited as well do the recruiting.
Healthcare
This is an umbrella term for anything related to medicine and patients and diseases. Starting from more efficient diagnosis to medical research, data science has started playing a pivotal role in this sector. It provides assistance with Image analysis and research for drugs. It is also found effective to use data science to enhance customer support and assistance.
Banking and Insurance- Fraud detection and risk assessment
Customer profiles, past applications and expenditures and many facets of personal information are collected by banks, esp for loans and insurance companies. This information if properly utilized can reduce fraud and can be used for risk assessment for loans and many other purposes.
This is where data science plays an important role and makes this process easier and identifies good risk and high-risk parties. Based on these predictions, bankers can easily select candidates to issue the loans. And, in a similar fashion, insurance companies can prevent being defrauded of money.
Marketing and advertising.
You can with all the data at your fingertips analyze and find out what your target audience should be to efficiently sell your service or your product. The data is used to gives demographics and interest based on which targeted advertising campaigns can be launched to convert potential leads into customers.
Airlines
The airline industry uses data science for flight path and route analysis. With a view to reducing operating costs and improving profitability and occupancy rates, airliners took to data science to predict and assess any expected delays to the flight timings, and drive customer loyalty programs.
Even the halts in between destinations and what planes to buy for higher ROI is something that is decided using the results of the data science algorithms.
Automobile industry
The Auto industry is now making strides in making driverless cars a commercial reality. A few companies have tested the technology and it is still being refined and assessed. This is a futuristic endeavour where data science along with ML and AI play a very important role.
Only with all the data of where what is and how it is to kind of data is made accessible to the technology can this type of experiment be a success. As is stands, there is a scope in the auto sector where data is used for driving loyalty programs, servicing of vehicles and customer experience with tech support and many more.
Virtual Reality and Augmented Reality
This is one of the more exciting premises in the future of data science. As such VR has a close relationship with data science esp in the gaming sector. The VR technology requires data and analysis to create a setup which reflects real life and yet you are able to function, up to a level, inside the virtual world.
This tech will require dependency of AI and ML. Once this tech becomes more commercially viable than it is today, data science has potentially an unlimited horizon to expand in this nascent field. The fields of artificial intelligence and data science are related yet worlds apart and similarly there are differences between machine learning and data science. Every field is interlinked and is used by the practitioners of the other to varying degrees and all this together makes this a very exciting enterprise to look forward to.
