The infamously tipped 'sexiest job of the 21st' century is a booming market with 97,000 data science and analytics jobs available in India alone, according to a recent study.
As the industry expands and evolves, there is also a growing need for more cross-functional data science teams with a wide range of disciplines in order for companies to realise the full impact of their data-driven initiatives. These professionals range from Data Analysts to DevOps engineers.
To put it simply, organisations are in need of more professionals who work at the intersection of data and business and who can prioritise business problems above all else.
Industry relevant curriculum = job-ready professionals
There is a huge talent gap, you hear it all the time and it is one of the biggest obstacles facing the industry right now. This has created extremely fierce competition between high growth companies, with major corporations slugging it out for the best in data science and analytics talent.
This has lead to a slew of learning & development initiatives aiming to nurture and retain the right talent and build high-performing cross-functional teams, drive a data-driven culture and lead transformational change.
While this has narrowed the gap, for now, many believe the best way to close the gap in the long term is through a more specialised curriculum. Some countries like India, for example, are yet to standardise data science education.
"It's time to reposition higher education for the new data economy by leveraging the varied and mammoth talent pool from under-graduate level onwards..." says Professor Krishnendu Sarkar, Director, NSHM School of Computing & Analytics.
Currently, the most coveted educational background is seen as an MS in fields ranging from engineering, maths and statistics.
However, the lack of standardisation has created a fragmented market. Professionals looking to transition into data science may find it hard to understand the requirements for a certain position, setting out on their own learning and development programme, which may not add value to the organisation in the end.
Ultimately, a standardised degree programme will aid students to follow a tailored curriculum that is more suited for modern-day organisational needs, while simultaneously building a healthy data science and analytics ecosystem.
Do you think that standardised education will close the talent gap forever? When it comes to hiring, will an MS in a non-specific field trump a bachelors degree that is tailored specifically to data science and analytics? I believe that it will but the real question is which one offers more value for money? Let us know what you think in the comments.