‘Data is the new oil’ – have you ever come across this mantra of the 21st century? I am sure you have. Big data, data mining, data management are all hot topics of the new world we live in. Every second, with every word we type on our mobile keyboards and with every picture we click on our mobile camera, megabytes of data gets transferred to the clouds. Calculating at this rate with every digital device and every single user, can you even fathom the amount of new data created by the time you’d have finished this sentence? Where is this data stored? Who manages it? How do you make use of this gigantic pool of data? Is it valuable at all? Answers to all these questions arises from a branch of science which is hardly two decades old, and we call it ‘data science’. This newbie in the realm of all sciences, however, happens to be the precious gem of our times.
What is Data Science?
Remember the last time you logged on to Youtube to watch a video? After you’ve finished watching, your feed would be refilled with further suggestions, claiming that the website has filtered several videos that match your viewing pattern, and some of those which most people watch. Similarly, you often get pop-up ads on Facebook, based on your interests and age group. And, haven’t you checked Google Maps at least once to see if your route has any unusual traffic? If you can relate to any of these examples, well, then you might already have realised the significance of a data scientist in the digitised world. Browsing history, purchase history and location history of each and every individual is data, which is stored and shared with similar platforms. It is from this endless loop of data that a scientist traces down patterns that can be used as cues to personalise your feed for further consumption.
Data Science, in simple terms, is the science of processing patterns and information from unstructured pools of data. A data scientist designs scientific tools to extract information from raw data, by implementing techniques of statistics, algorithms, and mathematical models. Their job is to simplify the process of understanding large sets of data, so that the data analyst can then decide how this data can be used for various purposes. To be honest, the job of a data scientist is not a cakewalk. All you have before you is an infinite expanse of data accumulated from different sources, and you are expected to create meanings out of it. Advanced understanding and interest in mathematics, statistics, machine languages, programming, database management are all necessary for a data scientist in making. You can choose any specialisation such as big data management, data visualisation, data engineering or machine learning, according to your liking.
How to become a data scientist: What are the courses?
Data science is a dynamic field of study that is growing every minute, which is why almost all the leading universities of the world now has a dedicated course to this discipline. In India, however, data science is yet to gain a recognisable status in the academia. It is indeed difficult to spot a prime institution in the country where you can seek a bachelor’s or master’s course with ‘data science’ as a title. Well, there are several private institutions that can provide MSc in Data Science. However, if you are determined to become a data scientist, then the first thing to recognise is that, you don’t really need a dedicated professional degree in data science to qualify as a seasoned data scientist. What you need to master is another set of technical and non-technical qualifications.
As we have already seen, advanced knowledge in mathematics and statistics is mandatory for a data scientist. That is, if you hold a master’s degree in mathematics or statistics from a reputed institution, that would be well and enough. If you choose the best of institutions to study statistics, then data science will definitely fall under your syllabus. In-depth knowledge or a professional degree in computer science will also help. A data science course, if you manage to enrol in a foreign university, extensively covers these three disciplines. These days, even qualified engineers with MTech degree choose to work with data science after undergoing boot courses.
How to become a data scientist: What are the qualifications?
Apart from being graduated from a reputed institution, the aspirant should also be equipped with knowledge in programming languages like Python, Java, Perl, C++ and Scala. SQL and NoSQL databases should be familiar as well. Analytical tools such as SAS, Tableau, Hadoop and R comprise another set of required expertise. Big data tools, machine learning techniques, algorithms will all be considered as additional skills. Other essential branches of data science such as predictive modelling, data mining, visualisation etc. can be learned through internships, individual projects, and online courses. Practice and experience are key qualifications for a data scientist.
In short, if you are a post graduate in mathematics, statistics or computer science with all the above mentioned knowledge, then you are ready to kick-start your career as a data scientist. However, leading recruiters including Google and Flipkart look for candidates with any of the following professional certification:
- Principal Data Scientist – DASCA
- SAS Certified Data Scientist
- Cloudera Certified Professional (CCP) Data Science certificate
- IBM Data Science Professional Certificate
- EMC Proven Professional Data Scientist Associcate (EMCDSA)
- Microsoft Professional Program Certificate in Data Science
These certifications can be acquired by giving several exams, if you are qualified enough. It has to be noted that most companies prefer post graduates and PhD holders as data scientists, and hence qualification in any of the core subjects is necessary for better job opportunities. IITs and IIMs provide several courses in computer science, data management and statistics where data science is an allied subject. Such courses should be your first preference.
Salary and Scope of Data Science Jobs
If you are hired as a data scientist, what kind of job are you expected to do? We have already seen that a data scientist is expected to design and manage scientific tools to extract information from unstructured data. But, this job profile has many layers to it. For example, you can focus on the designing of such tools. You can also choose to specialise in organising the data extracted by these tools. If you are interested in modelling and ideating, then you can also try your hand at visualising this data for the analyst to work on it. Data engineers work to build models to access data structures, data managers construct and maintain databases, and data architects design data platforms for firms. Along with these profiles, there is the conventional statistician who run tests using statistical tools. There are another set of experts called machine learning engineers who develop and implement algorithms. Besides them, there are data analysts and business intelligence professionals who work on par to connect the extracted information to corporate goals. Data science, in practice, is an umbrella term used to accommodate all these experts who deal with the mightiest tool now on earth.
All this workforce goes into classifying, organising and channelizing all the data stored in the clouds. Nations, armies, corporates, welfare organisations, medical systems, surveillance techniques and researches run on data and only data. Unlike the world before digital revolution, it is impossible to cut off this newly forged umbilical cord. E-commerce websites require more information on the purchasing pattern of their customers. Governments require personal details of its citizens. Corporate are in dire need of consumption patterns. Data stands as a one-stop solution for all. Isn’t it evident that a data scientist is most wanted person in all these realms? Job opportunities for data scientists is expected to shoot up in the coming years, especially in developing countries like India. The average annual salary in India for various job profiles that comes under data science is 8.18 lakh. This can go as low as 4 lakh, and as high as 20 lakh depending on the institution and nature of the job. However, there is no doubt that a data scientist in India earns a great deal than any other similar expert.
What if I tell you that almost 6% of the worldwide openings for data scientists are filled by Indians? Even though we do not have dedicated academic departments for data science, we are able to mould skilled data scientists with technical expertise. According to the reports, there are around one lakh openings for data scientists now in the country, and this will witness an exponential rise in the years to come. Big names such as Amazon, Google, Flipkart, Apple and IBM recruit hundreds of data experts every year with commendable salary. Many other major firms around the globe are now following the track to strengthen their footing in the battleground of data. When corporate veterans are now racing to take data science courses to educate themselves, why should we wait to join the game?