5 Roles In Data Science That Are Set For A Redesign

With emerging technologies like Artificial Intelligence, Machine Learning, Data Science, traditional skillsets are undergoing a huge transformation. There is also a more tech-centric approach for employers demand. According to NASSCOM, 1 million professionals have to be reskilled and 1 million potential employees and students to be skilled in the new emerging technologies. It has also been reported that the industry will face a shortage of 230,000 skilled techies as jobs in AI and Big Data are estimated to be 780,000 by 2021. Nasscom's IT-ITeS Sector Skills Council chief executive Amit Aggarwal said in a report that organisations are adopting the new and emerging technologies which will eventually transform the traditional job profiles into a higher domain with more automation and this change may cause a ripple in the $167 billion Indian IT services industry. In the latest survey, CEO of Shine.com, Zairus Master said, “As new job roles enter the market, we are already seeing job descriptions evolve. Skills which wouldn’t typically be found in the same role earlier are now being combined to create more multidimensional profiles. Hence, the traditional resume formats are now becoming irrelevant. Jobseekers will need to amplify the appeal of their resumes by highlighting the relevant job skills that they possess. For instance, data entry professionals will now need to acquire data science skills to be able to land high-value jobs.” In this article, we list down 5 IT job roles which are undergoing a massive transformation and require new skillset. Jobseekers, amplify your current skill-set by acquiring new data-driven skills.

1| Senior Data Science Leaders

The survey depicts that diversified job roles which require more wide-ranging skill sets are emerging. For instance, data related roles are fast-evolving as companies realize the importance of the goldmine of data they are sitting on. Therefore, companies are looking to hire Senior Data Science leaders who possess expertise in data science, and at the same time can understand the business and functional needs to create a strategic roadmap that can leverage the vast data collated by the company for business growth.

2| Data Engineer

Both old and new data are treasures to an organisation. A few years back, organisations didn’t use data as much as they use now. It is a different job role from data science but it is connected vitally with the data science field. The organisations are looking for skilled data engineers who will look after their massive data and help out the data scientists to extract meaningful information.

3| Data Virtualization

According to Gary Chen, research manager, IDC's Software-Defined Compute, "Virtual machine software continues to be a foundational technology even as customers move to cloud architectures and containers. The virtual machine software market has been remarkably resilient and will continue to grow positively over the next five years, despite being highly mature and approaching saturation." Decision-makers are investing heavily in this concept, and staffs are seeking out these skills. IDC forecasts it to increase at an average pace of 4.6% from 2017 to 2022.

4| Analytics And Data Management

With the increase in data in organisations, the data-driven organisations are in need of good analysts and data management enthusiasts. According to the report by International Data Corporation (IDC), "The fastest way for any organization to become data-centric and data-driven is to deploy an intelligent data management tool," said Amita Potnis, research manager, IDC's Storage Systems program. By 2025, 163 zettabytes (ZB) of data will be created which is 10 times the number that was created in 2016. IT professionals with analytical and data management skills will be tasked with helping organizations solve problems and make more informed evaluations.

5| Machine Learning Engineers

With the trending of this field, computer science engineers are slowly shifting their jobs towards this field. Machine learning is becoming an integral part of the organisations who play with data every day. According to Deloitte Global, the number of machine learning pilots and implementations will double in 2018 compared to 2017 and double again by 2020. International Data Corporation (IDC) also predicted that spending on AI and ML will grow from $12B in 2017 to $57.6B by 2021. The organisations are looking to hire more machine learning engineers who pose to have skilled knowledge in this field.