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Published on June 28, 2019 | Choosing a Career| Unheard avenues
AI Myths and Realities: AI Careers


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Upcoming Technologies

In a recent blog, we pointed out the scope, perspective and development of Artificial Intelligence as an applied technology. We also talked about the nuances of Big Data-driven applications of Artificial Intelligence via neural nets, cognitive AI, deep learning and machine learning. These new technologies have immense potential and are being applied on a daily basis across the internet and through smart devices. Google, Microsoft, Apple and many more tech firms in Silicon Valley are investing and researching in these technologies. According to the International Data Corporation(IDC), investments in these technologies will mount to $52.2 Billion in 2021.

“Interest and awareness of AI are at a fever pitch. Every industry and every organization should be evaluating AI to see how it will affect their business processes and go-to-market efficiencies.” David Schubmehl, research director, Cognitive/Artificial Intelligence Systems at IDC.

According to the IDC Worldwide Semiannual Cognitive Artificial Intelligence Systems Spending Guide, retail will overtake banking in 2018 to become the industry leader in terms of cognitive/AI investments. Retail firms will invest $3.4 billion this year on a range of AI use cases, including automated customer service agents, expert shopping advisors and product recommendations, and merchandising for omni channel operations. Much of the $3.3 billion spent by the banking industry will go towards automated threat intelligence and prevention systems, fraud analysis and investigation, and program advisors and recommendation systems. Discrete manufacturing will be the third largest industry for AI spending with $2.0 billion going toward a range of use cases including automated preventative maintenance and quality management investigation and recommendation systems. The fourth largest industry, health care providers, will allocate most of its $1.7 billion investment to diagnosis and treatment systems.

All these investments mean that a variety of specialist career opportunities are mushrooming in this field. A career in artificial intelligence can be realized within a variety of settings including private companies, public organizations, education, the arts, healthcare facilities, government agencies and the military. Some positions may require security clearance prior to hiring depending on the sensitivity of information employees may be expected to handle. It is expected that Careers in Artificial Intelligence will be at the heart of new IT developments in areas like automation, Dev-Ops platforms, the Internet Chabot, and robotics.  

Artificial intelligence (AI) will have a large fundamental impact on the global labour market in the next few years. Therefore, the discussion will shift to legal, economic and business issues, such as changes in the future labour market and in company structures, impact on working time, remuneration and on the working environment, new forms of employment and the impact on labour relations. As mentioned earlier AI and automation are here to stay. The question we now need to answer is, will intelligent algorithms and production robots lead to mass unemployment? In addition to companies, employees, lawyers and society, educational systems and legislators are also facing the task of meeting the new challenges that result from constantly advancing technology.

Economics always wins, AI and automation are taking over industries as they are economically better feasible than any other workforce in given industries.

Hence instead of fighting this change, we must adapt to it. Why try swimming against the tides of innovation when we could just grab our surfboards and ride it through. Below we have listed out a few possible careers in the field of artificial intelligence and what it would take to secure those careers.

Types of Careers in Artificial Intelligence

 Academic Careers:

Such a career means pursuing research or PhDs with a motivation to learn more and pursue excellence in a scientific manner.

Professional Careers: 

An industry career that leads to self-improvement through experience and problem-solving tasks. Specialist tasks will include agent-oriented intelligence gathering and also developing algorithms and applications to direct such processes. Consultation based on situation to situation is also an emerging platform for a professional career. People choosing such a career will attain peaks and perks.

Some specific professions sought after in this growing field are-

1. Machine Learning Engineer

In great demand, machine learning engineers have to sift through massive data sets. This requires them to possess strong software skills, apply predictive models and implement natural language processing. They must also be able to develop software and have to have familiarisation of modern development tools right from IDEs like Eclipse and IntelliJ to the components of a continuous deployment pipeline. They must also have the practical skills required for executing such solutions.

Preferred Qualifications: 

  • Masters or doctoral degree in computer science or mathematics.
  • Working knowledge of modern programming languages like Python, Java, and Scala.
  • Strong computer programming skills, expert mathematical skills. 
  • Knowledge of cloud applications and various computer languages.  
  • Excellent communication and analytical skills. 

2. Robotic Scientist

For robots to able to automate jobs, programmers are required to work behind the scenes to ensure optimum performance and functionality. Multiple tasks in space exploration, healthcare, security and many other scientific fields are being automated with the help of robotics. Robotic scientists are required to create and maintain mechanical devices and/or robots that perform tasks with or without human interaction. The main skill required in this field is to be able to write and manipulate complex algorithms that interact with electromechanical transducers. Collaborative skills are also important to integrate several technologies to develop a prototype.

Preferred Qualifications: 

  • A bachelor’s degree in robotic engineering/mechanical engineering/electro-mechanical engineering/electrical engineering.
  • Specializations in advanced mathematics, physical sciences, life sciences, computer science, computer-aided design and drafting (CADD), physics, fluid dynamics and materials science and related certifications. 

3. Data Scientist

Data scientists collect, analyse and sift through vast amounts of data by using machine learning and predictive analytical tools to gain insights beyond the usual statistics. They should have practical experience and expertise in using Big Data platforms. Expert knowledge of tools including Hadoop, Pig, Hive, Spark, MapReduce, programming languages including structured query language (SQL), Python, Scala, and Perl, as well as statistical analysis languages.

Preferred Qualifications:

  •  Master’s or doctoral degree, though an advanced degree in computer science is preferred, it is not a prerequisite.
  • The most desired technical skills are in-depth knowledge of SAS and/or R, Python coding, Hadoop platform.
  • Experience working on cloud tools like Amazon’s S3 and the ability to understand unstructured data.
  • Non-technical skills required include strong communication and analytical skills, intellectual curiosity and business acumen.

4. Research Scientist

Research scientists need multi-disciplinary expertise and knowledge in the fields of machine learning, computational statistics, and applied mathematics. Having the necessary skills to probe into data representation, natural language processing, computer perception, reinforcement learning, graphical modelling and deep learning.

Preferred Qualifications: 

  • A master’s or doctoral degree in computer science, or in a related technical field or equivalent practical experience is the basic requirement for this role.
  • Skills such as parallel computing, artificial intelligence, machine learning, knowledge of algorithms and distributed computing and benchmarking.
  • An in-depth understanding of computer architecture and strong verbal and written communication skills.

5. Business Intelligence Developer

Business intelligence developers primarily analyse complex data and look for current business and market trends.  Their job is to increase profits and efficiency of the organization. They need to have strong technical and analytical skills, sound communication and problem-solving skills. They need to have the necessary skills for designing, modelling, building and maintaining data analysis tools for complex, extensive and highly accessible cloud-based data platforms.

Preferred Qualification:

  • A bachelor’s degree in computer science, engineering or a related field is required.
  • A combination of certifications and on-the-job experience are preferred for this role.
  • Experience in data warehouse design, data mining, knowledge of BI technologies, SQL queries, SQL Server Reporting Services (SSRS) and SQL Server Integration Services (SSIS) would also be essential and extremely beneficial.

The above-mentioned specialisations are just the tip of the iceberg. There is no doubt that AI is here to stay, and who knows, maybe in a few years’ time, there will be some other technology even more powerful that would hog the limelight and take center stage to every discussion. While the future remains unpredictable the IT age will play an extremely pivotal role in it. Historically innovation has always lead to fairer means of livelihood, with automation and AI do you think that will also be the case? Let us know what you think. Reach out to us at Navigus.in and to read more check out our channel and various other blogs.

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