Realising the role that data science is going to play in business in the coming years, every B-school has started offering a STEM classified masters programme in analytics, says Abhijit Dasgupta

Till 2018, in India and elsewhere, a degree programme in data science was only available at a graduate/masters level, primarily in USA. Graduate students (Masters and PhD), over there, would be taking specialised courses on big data engineering, artificial intelligence, machine learning, data mining, statistics to gain understanding of shifts in innovation that’s getting powered by data science. Realising the importance that data science is going to play in future of the business in years to come, every top B-schools (mostly US universities) started offering a STEM (science technology engineering mathematics) classified Masters programme in analytics.

While the pieces of technologies and methods were there since  1950, the ideas were mostly in the realm of well-funded laboratories using proprietary systems. The advent of big-4 (Google, Facebook, Microsoft, and Amazon), Apache Foundation and other open source contributors changed the game and made data science as part of everyday life of a professional.

The careers in data science are originating from four different but well-connected streams:

• Computer Science
• Statistics
• Mathematics
• Business Analytics

However, the entire chain of innovation is led by engineers who are working for the likes of Google and Amazon, hence there is a disproportionate influence of Computer Science engineers in this area.

The careers that a graduate of data science can pursue are as follows:

• Data Engineers
• Data Scientists
• Data Analysts
• Business Analysts

Apart from the traditional roles of Software Engineering and modern roles of Cloud engineering, DevOps engineering: those are available to him/her. Traditionally, Data Engineers are pegged at the highest salary bucket.

Typically the qualities or qualifications that companies look at a recruit are:

• Object Oriented Programming skills (Java/Python)
• Functional Programming skills (Java/Scala/Go)
• Top Coding skills (specifically data structures & algorithms) in any language
• Good understanding of Probabilities & Statistics
• Strong foundation of Mathematics
• Optimisation
• Distributed Computing and Operating systems
• Machine Vision
• Machine Intelligence packages (such as Tensor Flow, Keras etc.)
• Strength in JavaScript for Visual Analytics (packages like Tableau)
• Cloud and DevOps
• Some understanding of Business Domain (eg Retail, Transportation, Healthcare and  Finance: which can be gained through capstone projects, dissertation, thesis etc.)

It is unlikely that someone would combine all the above qualifications, but one has to find his/her own sweet spot and try gain competitive strength in three or four skills above.

Top B Schools offer undergrad programmes on data science and many of the courses and topics actually are from a typical Computer Science Master programme; and therefore the rigor is unparalleled.

The students typically benefit from the 2X or more salary differential (vis-à-vis a comparable undergrad course in engineering) and have a jump-start career; and in case, s/he is able to crack into the big league of Google, Amazon, FB, Microsoft, then this differential goes up to 5X at the start of the career. Secondly, the graduates also get to work on the most happening technologies in the world thus improving their professional profile significantly. A job is not only defined by the salary, but also by the content and contribution to humanity and global impact.

The writer is Director, Data Science Programmes, SP Jain School of Global Management