For years, Artificial Intelligence has managed to transform various global industries and change our lives by a significant leap. Throughout it’s history, it has been constantly developing and branching out to subfields addressing different issues and breakthroughs in science and technology.
As it continue to offer promising tech innovations such as smart visual assistants, automated health diagnosis systems, and data analysis marketing programs, the opportunities under the discipline are endless. In a 2018 study, Indeed, one of the most widely-known job sites across the globe, has recorded a significant rise in demand for AI-related roles and positions under a variety of different sectors like education, health, and business.
So if you’re up for fulfilling experiences in your career growth, pursuing a professional path under AI may be what you need.
So what exactly are the different Artificial Intelligence career paths that are currently in-demand today? Let’s have a look at some of the most popular AI jobs.
In data science, the role of big data is of utmost important as patterns and models of massive data, along with the inferences one can make from them, that can significantly affect a company’s revenue or overall financial state.
Data Scientists gather these data and analyze them through the knowledge and skills they have learned and acquired from mathematics, statistics, advanced analytics, machine learning, and of course, artificial intelligence. They can be part mathematicians, part computer scientists, and part pattern or trend-spotters all at once. But more specifically, they use the inferences from analyzing data to create insights and recommendations that can be used for the company’s advantage.
Due to the job’s wide scope on multiple disciplines, they are highly sought out in different industries, most especially in the IT and business fields.
Machine learning is a significant subfield under AI. It primarily deals with programming smart machines to learn and perform specific tasks it was designed to do, one of the basic and fundamental ‘criteria’ that can determine whether a system or program is a smart AI. This makes machine learning engineering a crucial field in multiple technology-led industries.
Machine learning engineers are responsible with researching and developing smart machine innovations. The job plays a crucial role in most companies’ tech projects that require professional expertise in the discipline. It requires the knowledge and skills of a software engineer, as well as the experience of a data scientist and data engineer. Machine learning engineers work mostly with algorithms, codebases, datasets, predictive models, and various other programming languages to create an effective and smart AI system.
Business Intelligence Developers simply make data understandable and advantageous for businesses. Their core and essential goal is to analyze complex data sets and arrangements to recognize market patterns that companies can use to their advantages.
Upon utilizing unique business intelligence tools and reaching the end of the analysis process, business intelligence developers will come up with insights that can provide detailed intelligence and professional assistance .
The job requires solid technical and analytical abilities, as well as strong critical thinking skill.
AI research is one of the most leading subfields at present.
AI research scientists hold an extensive list of roles and responsibilities. They must manifest a certain level of expertise in different AI-related fields such as applied mathematics, computational statistics, algorithms, machine learning, and deep learning. They must also have extensive knowledge, skills, and experience in research methodologies, research analysis, computer perception, graphical models, and reinforcement learning.
Big Data Engineers and Architects often work along with data scientists with massive data as the core of their roles and responsibilities. They translate data to allow transparent communication between parties involved in businesses.
In comparison to data scientists, big data engineers and architects are more involved in the entire process as they are commonly required to plan, design, and develop data environments themselves.
AI Engineers and Architects both offer solutions to clients and are responsible in building and keeping architectural structures by utilizing leading AI-driven technology frameworks. They must hold a substantial knowledge under artificial intelligence, and thus are crucial operators in architectural projects.
Similar to chief data scientists, they plan the implementation of solutions, make decisions, and evaluate every issue along the process. They must have a good understanding on each client’s needs to address the issues accordingly and be flexible to make any changes from the client’s end, and translate concerns to plausible business solutions.
Software engineering is a branch under computer science and primarily deals with building and developing computer systems, applications, programs, and software. These include web browsers, operating systems, and database programs in computers that you use in a daily basis.
People’s reliance on the ever-growing technology results in a lot of investment in software engineering. This eventually made software engineering a subfield where opportunities are constantly growing. Because of this, software engineers play a significant role in the development of AI.
Software Engineers must have extensive knowledge and skills on programming languages, software development, and computer operating systems. They also use mathematical analysis that require engineering and computer science knowledge. They must also hold great expertise on software creation, and be able to utilize engineering concepts freely and customize them to fit each client’s unique needs.