Describe Your Job Profile Example for Software Engineer

Since 2015, demand for AI roles such as machine learning engineers has risen by 344%, while demand for data scientists has jumped 78%. UI and UX designers fall under the category of AI careers, as do full-stack developers, software engineers, big data engineers, research scientists and more. More recently, roles including process automation specialist and data ethics officer have emerged and are growing in demand.

As you’d expect, these roles require a set of hard skills in order to be able to handle and analyze data and program the software, yet the level of technical knowledge varies depending on the role. Plus, these roles are increasingly relying on a mix of other softer or more general skills that many people looking to get into a career in AI may not realize they already have.

In the government report in May, employers were asked which were the most important skills that their companies needed to improve on. Their top 10 wish list was as follows:

·       Information management

·       Knowledge of emerging technologies and solutions

·       Data communication skills

·       Communication

·       Database management

·       Data literacy

·       Data ethics

·       Analysis skills

·       Analytical mindset

·       Adaptability

What’s more, the top five priority skills businesses want to improve in the context of working with data include communication, professionalism, problem-solving, data ethics and then basic IT skills.

As both lists attest, knowledge and communication skills are now up there with the technical, day-to-day know-how. Getting into a career in AI in the early days largely relied on knowledge of very precise programs. Getting into a career in AI in the years and decades to come is going to more heavily lean on the interplay between humanities and science.