With the emergence of technologies, there are speculations that it will eliminate human jobs. Sudeshna Datta tells you how one can work along with technology

With the advent of emerging technologies such as artificial intelligence (AI), machine learning (ML), natural language processing (NLP) and big data, the jobs of today are going through major transformations, where machines are gaining greater prominence in daily business functions. This has also given rise to a large number of new career opportunities, both in terms of product innovation and optimising operations for a more effective output. As a result, the skills required by employees are changing, too, giving rise to the need for reskilling and up skilling the workforce in order to meet the new demands.

Given that emerging technologies are bringing about widespread changes within the job landscape, there has been some speculation about the extent to which automated tools will eliminate human jobs. The fact remains that the growing number of careers in AI and related fields will actually be a boon in terms of catering to the needs of an increasingly digitised business ecosphere.

The new roles are also bringing about the demand for new or realigned skill sets amongst the workforce, and there is a considerable shortage of talent in the tech industry with the necessary skills. However, due to the growing demand, several amongst the IT industry talent pool have begun considering it as a lucrative career choice. There are several existing options, and others to be created in the near future, for those looking to join the industry in an AI or ML role.

Before considering a job in AI, it is a good idea for aspirants to build a strong foundation in skills such as coding in various commonly-used languages, statistics, cognitive science theory, engineering, robotics and Bayesian networking. Here’s a list of some of the most in-demand jobs in the industry at present:

• Machine Learning Eng

In order to effectively carry out the role of a machine learning engineer, it is important to be well-versed with AI programming and have a deep understanding of multiple coding languages. ML professionals should also be privy to the practical application of predictive models and natural language processing.

• Data Scientists

In a world that is fuelled by all-things-data, these professionals are the ones who make sense of it all to put forth useful insights and information for a business. For this, data scientists must have a thorough understanding of statistical computing and programming languages, as well as good communication skills in order to effectively present insights to various stakeholders. Using tools such as machine learning and predictive analysis, the role of a data scientist is to collect, analyse, and interpret complex and large pools of data.

• Research Scientists

The role of research scientists are vital to gathering and interpreting data that is relevant to a particular business. They must also be highly experienced in AI disciplines across the board such as ML, applied mathematics and computational statistics. Their expertise should lie in the key areas of graphical models, reinforcement learning, NLP and computer perception.

• Robotic Scientist

Building a robot requires a professional with specific knowledge and skillsets. In order to become a robotic scientist, one will need a bachelor’s degree in computer science, engineering or similar fields. A robotic scientist creates mechanical devices that can carry out a number of processes and functions as per the requirement.

AI is optimising operations, thus helping businesses do better while cutting costs, and helping employees focus on tasks that create more value and aid to their  growth. By focusing on  revamping their skillsets for the future of jobs, aspirants can secure their dream jobs while effectively contributing to their personal growth and that of their organisation as well.

The writer is Co-founder & Executive VP, Absolutdata Analytics