India 
USA 
The 21st century is the age of automation and competition. Companies are using artificial intelligence (AI) to survive, differentiate and thrive. AI comes into play in diverse sectors. AI and other emerging technologies are freeing up the time spent on managing tasks and transactions that were done manually.
69% of managers’ work to be completely automated by 2024 ~ Gartner
This, in turn, has given rise to many career opportunities. Take a look at these top five opportunities in AI that you can look forward to in 2020 and the competencies it takes to fulfill such job roles.
Research Scientist
It helps to have good knowledge about deep learning, machine learning, benchmarking, and distributed computing. Knowledge of parallel computing would serve as a splendid bonus. Then again, you must display extensive experience in handling graphical models, computer perception, natural language processing and reinforcement learning.
Now, professional responsibilities depend upon your area of interest or your previous experience in research.
Business Intelligence Developer
Your role here would be to study and analyze complicated data sets for identifying market and business trends. Your company would expect you to be the major decision-maker, thereby enhancing its effectiveness and profitability.
As a leader, you will manage tasks (design, model and maintain) related to complicated data. You may access everything via the cloud. Apart from your basic qualifications, you will need additional certifications, as well as some hands-on experience too. In other words, you must have a good knowledge of BI technologies, data mining, data warehouse design and SQL (server reporting services, server integration services and queries).
Machine Learning Engineer
Do you have a background in data science and applied research? Then, you would be ideal to handle AI projects. Of course, you will need to build knowledge of AI programming too. Similarly, the knowledge of programming languages (Scala, Java, Python, etc) will help.
A Machine Learning Engineer helps set up and maintain platforms for machine learning projects. The role requires an amalgamation of knowledge of machine learning, computer programming, neural networks, deep learning, analytical skills, with software development tools, cloud applications and agile development practices. Strive to bring natural language processing and predictive models too into play when handling humongous data sets.
Head of Business Unit
The head of a business unit, understands the business processes that are critical to setting-up real-world scenarios and tangible outcomes. AI leaders will engage in processes that focus on leading the programmers of the AI machine as well as influencing decisions made by machines after the programming is completed.
Data Scientist
What do you need to be a successful data scientist?
Firstly, you must be comfortable working with certain tools and platforms. They include Spark, Hadoop, Pig, Hive and Map Reduce. Similarly, you must have excellent knowledge of certain programming and statistical computing languages. They include SQL, Perl, Scala and Python. Thirdly, your organization would expect you to have at least a couple of years of experience at working with machine learning.
What will your responsibilities be at work?
By combining the skills of predictive analytics and machine learning, you should find it easy to handle complicated datasets. For one, you will have to gather, analyze and interpret large amounts of data. Secondly, you will have to design algorithms, which will improve the collection, as well as cleanse of data, for proper analysis. Once you finish your analysis, you will have to communicate your findings to the business leaders in your organization.
Now, such high expectations can leave hopefuls from non-AI backgrounds feeling disheartened! Fortunately, with the help of effective learning and guidance, they can get into the same companies as AI experts do. For instance, the Advanced Certification in AI/ML from IIIT Hyderabad has helped thousands of professionals from hundreds of leading organizations get deep tech knowledge in this space and relaunch their careers.
It is time to embrace the revolution.
