So, you want to work in Artificial Intelligence?
The world, more and more, is leaning heavily toward automated processes, the ease of artificial intelligence (AI) and the support of machine learning. As a result, job opportunities are increasingly prevalent in those areas.
AI is used in almost every industry, presenting a viable platform for career opportunities as more and more brands and businesses adopt its functionality to streamline their operations and processes. Designed to support the human workforce by doing the mundane jobs we trawl through in a fraction of the time and enable businesses to cut costs, boost research and drive innovation; AI is constantly growing, propelled forward by skilled professionals seeking to further advance the power of AI and its capabilities.
Starting from the accomplishment of a bachelor’s degree in subjects including computer science, maths, information technology, statistics, finance or economics; individuals wishing to work in AI should be looking to fine-tune their technical skills. Those starting out in the field of Artificial Intelligence must be highly experienced in the art of computer skills and as with the majority of analytics jobs, knowledge of one or more programming languages is a must-have. So get to grips with the likes of C++, R, Python and Java.
Relevant industry certification for careers in artificial intelligence should centre on courses in machine learning, deep learning and data science. Though education aside, the need for practical hands-on training is incredibly important for those who are new to the field and applying to entry level and junior roles in AI.
Individuals coming from programming roles will find the most straightforward career trajectory, moving with ease into an AI position. Working in AI requires a strong understanding of algorithms, something programmers are already familiar with. Data Analysts and Data Scientists will also have some programming knowledge that can be applied to jobs in Artificial Intelligence. AI also requires experience with neural networks and familiarity with electronics and robotics in order to work with the machine learning subset of AI which supports the mechanism in its learning. Thus it is imperative to know how to prepare data as well as being able to demonstrate strong proficiency in model building and data visualisation, all transferable skills between the roles of data science and AI.
While the technical skillset is crucial, there is an equal importance for AI professionals to assess their practice within the larger context of the business itself and its needs and ultimate goals. On the business end, individuals who are able to think creatively and apply analytical thinking to solving problems will find themselves aptly suited to a career in AI. Furthermore, no matter which industry you take an AI role in, effective communication is key.
In terms of the specific job types you can refine your search towards, these are among the most common:
- AI Engineer, which has an average UK salary of £53,000 per annum, $141-168,500 in the United States and €61,961 in Europe.
- Data Mining and Analysis Specialist, which has an average UK salary of £52,500 per annum, $60,639 in the United States and €49,906 in Europe.
- Machine Learning Engineer, which has an average UK salary of £68,772 per annum, $138,101 in the United States and €52,431 in Europe.
- Data Scientist, which has an average UK salary of £52,714 per annum, $113,436 in the United States and €58,800 in Europe.
- Business Intelligence Developer, which has an average UK salary of £35-40,000 per annum, 96,823 in the United States and €42,000 in Europe.