Currently there are 45,000 job openings related to Artificial Intelligence (AI), with data scientists and Machine Learning (ML) engineers in India when it comes to the most in-demand careers.
A report by TeamLease Digital, a tech staffing company, showed these findings which analysed the potential of AI across several industries. As per the report, the increased focus on the scalable ML applications is leading to a surge in demand for AI professionals who are proficient in scripting languages and capable of building conventional ML models.
Following are some of the findings from the report:
• Data and ML engineers can earn up to Rs 14 lakh per annum, while data architects can get up to Rs 12 lakh.
• Those who have eight years of experience in similar fields can earn even higher salaries ranging from Rs 25 to 45 lakh per annum.
• It has become increasingly important to upskill oneself with AI skills when it comes to the career growth and employability. There are going to be long-term benefits for individuals and their careers who invest in AI skills
• In order to build an AI-ready workforce, 37% of the organizations prefer to provide their employees with relevant tools, whereas 30% of organisations stated AI learning initiatives are mandatory to unlock hidden talents in the workforce.
• As much as 56% of the organizations also express that the necessary initiatives are being undertaken to fill the AI demand-supply talent gap.
What Exactly Do These People Do?
Data Engineer: These engineers collect data from multiple resources and in turn convert them as well as build and manage systems that generate this data.
They clean and transform the procured data for data scientists and analysts to scrutinize. In order to build the architecture and data systems, they use the same guidelines like the ones used for software development by making the data viable by writing complex queries.
They also have knowledge of algorithms and some of the important concepts in programming.
ML Engineer: A ML engineer is one who focuses on researching, building and designing self-running artificial intelligence (AI) systems to automate predictive models.
They design as well as create the AI algorithms capable of learning and making predictions that define machine learning (ML).
Data Architect: Tasked with defining policies, procedures, models, and technologies that will be used to collect, organize, store, and retrieve information for the organization.
An expert who formulates the organizational data strategy, including standards of data quality, the flow of data within the organization, and security of data. It’s the vision of this data management professional that converts business requirements into technical requirements.
