PLAYING with NUMBERS
After engineering and medicine, data science is the hot career trending. Here’s why it is in demand.
In the last few years, we have probably created more data digitally than in the rest of human history. Think about the millions of Internet searches and social media posts that are made every minute, and the resultant data that corporations and governments are collecting on consumers and stakeholders.
What do we do with this information?
This sea of data can overwhelm us; we must learn to tame the data deluge to our advantage. Our key challenge is to filter out the signal from the noise and make sense of the data that is being accumulated every second in this digital era. The discipline of data science is a blend of statistical and computational tools, algorithms and machine learning principles with an aim to uncover hidden and relevant patterns in raw data, which are then used to drive informed and better decisions.
Career of the future
Data scientists can help their organisation make better decisions in several respects reducing downside risk and adding value. Data science skills are likely to give graduates an increasingly competitive edge for employment in the years ahead. Organi
sations across sectors are starting to change the way they use data to develop new solutions by investing, not only in data science talent, but also in people who can build big data infrastructure, data curators, data translators and subject matter experts. With data science becoming an imperative area of work for almost any organisation, in any sector, and of any scale, it is a very exciting time to study and master the discipline.
Skills needed for data science
The primary skill that a person will need is a quantitative mindset— an affinity with numbers and the ability to understand them to derive rational conclusions. Some specific skills that a data science aspirant should start building on at a young age include data visualisation, business intelligence, data modelling, and business analytics. As a discipline, data science cuts across domains, and is at the intersection of mathematics, computing, statistics and knowledge of the domain of application. One might be a lawyer, a marketer, a healthcare professional, or a public policy expert, but valuation in their respective industries will increase manifold if one applies knowledge of data science to drive better decision making.
Job openings after data science
The number of jobs in data science and related fields is expected to explode in the coming years. By 2020, an estimate of about
2.7 million positions will be on the market, while the size of the analytics, data science and big data industry in India is expected to grow seven-fold and reach about 20 million by 2025.
There are a number of opportunities as data scientists, data analysts, data architects, statisticians or business analysts across industries including e-commerce, healthcare, financial services, sports, journalism and public policy. GlaxoSmithKline, for instance, is using data science to improve their success rates and help bring medicines to patients. At the same time, Amazon (and almost every other e-retailer) is employing data scientists by the dozen to understand consumer behaviour trends and improve the shopping experience. This also makes data science the most useful skill for anyone in a managerial position in a corporate sector firm.
Inclusion in higher education
A lot of higher education institutions and e-learning platforms have launched degree, diploma and certificate courses in data science and business analytics. However, most of these programmes focus on imparting technical knowhow of software such as tableau and stata. What the majority of courses lack in their curricula is the application of this knowledge in solving real-time problems.
A professional who only knows how to crunch numbers without knowing how to apply those inferences in terms of decision making will remain a pure technician, severely limiting growth prospects even within the realm of data science. The ideal course will, therefore, equip students with the technical know-how as well as guide them to draw better insights to improve decision making for businesses.
In India, while engineering institutes such as Indian Institutes of Technology (IITs) and National Institutes of Technology (NITs) have launched executive programmes in data science, social science and management schools have also begun to add data science to their portfolio of offerings, examples being Tata Institute of Social Sciences (TISS), Mumbai, and Indian School of Business and Finance (ISBF), Delhi. The inclusion of data science in these social science programmes means that students receive training in not just the quantitative, statistical and programming aspects, but also understand the application of data science to become better decision makers.
Internationally, one of the most exciting places to study data science would be LSE (London School of Economics), UK, which now offers an M Sc data science programme. Across the Atlantic, some prominent institutions offering these programmes include Carnegie Mellon University, Stanford University and Georgia Institute of Technology.
The primary skill that a data science aspirant will need is a quantitative mindset