Career Prospects in Data Science and Artificial Intelligence

Data science and artificial intelligence are revolutionizing the business world, ranging from small businesses or startups to large multinational companies and even public administrations. The demand for data scientists and AI engineers will grow significantly in the coming years, given the increasing amount of data generated and the need to use this data to solve real-world problems. The World Economic Forum estimates that by 2025, 58 million jobs related to Data Science and Artificial Intelligence will be generated. 

Companies like Google, Microsoft, Amazon, and Facebook have invested heavily in data science and AI. They are looking for skilled professionals to help them develop and deploy machine learning models, build and maintain data pipelines, and analyze data to identify trends and patterns. Data science and AI are skill-based careers, meaning you must constantly learn and update your skills to stay ahead of the curve.

Career Outlook for Data Science Professionals

We are in the middle of the 4th Industrial Revolution (Industry 4.0), mostly driven by Data Science. This ever-growing field involves collecting, analysing, and exchanging lots of data! The demand for professionals for various data science jobs is at an all-time high, as is the supply gap.

BLS suggests that professionals with computer science, Math, and finance backgrounds will have an incredibly powerful advantage to grow in a career in data science.

• Connect data sources and automate acquisition mechanisms to update the information repository.
• Run processes that clean the obtained data and check for inconsistencies, eliminating redundant and erroneous data and generating summary information across different projects.
• Explore data to discover patterns, detect anomalies, test hypotheses, and verify assumptions through different data science tools, statistical formulas, and graphical representations.
• Apply different techniques like machine learning, statistical modelling, deep learning, data visualization, and artificial intelligence to draw insights and make predictions useful to achieve long-term and short-term business goals.
• Check the findings and predictions obtained in the previous step against reality and present them in a convincing way. This does not require scientific skills but rather the ability to communicate effectively.

Career Outlook for Artificial Intelligence Professionals

Artificial Intelligence Professionals train Artificial Intelligence systems to capture and process the data that provide solutions to various industrial, commercial, and professional activities. Since Artificial Intelligence is an area in full development, these professionals can research new applications to innovate. In the coming days, artificial intelligence professionals will collaborate with engineers, agricultural professionals, scientists, the banking system, doctors, biologists, HR professionals, IT systems, statistics, marketing, managers, economists, and even startups.

Now the question arises: what are the on-job roles of artificial intelligence professionals? So some of the common job roles of artificial intelligence professionals are –

• Design, develop and implement Machine Learning techniques (automatic learning) for their applied use through predictive models, recommendation systems, scoring, and recognition of segments and clusters.
• Build analysis sequences using vigorous data libraries and can even build your own libraries for applications in different industries.
• Build neural networks and successfully lead Machine Learning projects that allow computer vision to be implemented and applied to image data.
• Apply AI to process audio and text from applications that allow, for example, automatic speech recognition, music synthesis, chatbots, automatic translation, and natural language understanding, among other possibilities.
• Use cybersecurity tools considering both the possibilities of attack and errors in the requirements, implementation, or deployment, as well as taking into account the confidentiality of the data supplied by the user.

Where Will You Work?

Data science and artificial intelligence (AI) professionals can work in a variety of industries and settings, including:

• Technology: Tech companies are at the forefront of data science and AI innovation, and they hire many data scientists and AI engineers to develop and deploy new products and services. Some examples of tech companies that hire data scientists and AI engineers include Google, Microsoft, Amazon, Facebook, and Netflix.
• Financial services: These companies use data science and AI to improve their risk management, fraud detection, and customer service. Some examples of financial services companies that hire data scientists and AI engineers include banks, hedge funds, and investment firms.
• Healthcare: Healthcare companies use data science and AI to develop new drugs and treatments, diagnose diseases, and improve patient care. Some examples of healthcare companies that hire data scientists and AI engineers include pharmaceutical companies, hospitals, and medical device companies.
• Retail: These businesses use data science and AI to improve their product recommendations, inventory management, and supply chains. Some examples of retail companies that hire data scientists and AI engineers include Amazon, Walmart, and Target.
• Manufacturing: Data science and AI help manufacturing companies improve their product quality, reduce costs, and predict machine failures. Some examples of manufacturing companies that hire data scientists and AI engineers include Tesla, General Motors, and Siemens.

Career Trajectories in Data Science and Artificial Intelligence

The future of Data Science and Artificial Intelligence holds a lot of potential. Let’s take a look at some of the popular job profiles in these fields –

Data Science

• Data Scientist
• Data Architect
• Data Science Manager
• Principal/Chief Data Scientist
• Data Analyst
• Data Warehouse Engineer
• Business Intelligence Developer
• Computer Vision Engineer
• ML Specialist
• Python Programmer – Machine Learning
• Data Scientist – R/Statistical Modelling

Artificial Intelligence

• Machine Learning Engineer
• Data Scientist – Machine Learning/AI
• Senior Business Analyst – Machine Learning
• Artificial Intelligence Solution Leader
• Lead – Advanced Analytics & Artificial Intelligence
• NLP Developer – Machine Learning/AI
• Data Scientist (Artificial Intelligence)
• Artificial Intelligence/Machine Learning Engineer
• Speech Scientist – AI/Machine Learning
• Artificial Intelligence/ Machine Learning Lead
• AI Scientist – Deep Learning
• Business Analyst – Artificial Intelligence

Conclusion

Data science and artificial intelligence have penetrated almost every domain, and it’s high time to decide and make a smart career move to these domains. Companies seek candidates with competencies in core data science and artificial intelligence concepts, statistics, computer science and programming, data structures, algorithms, system design, and storytelling. Having said that, Data science and artificial intelligence are not easy fields, and you must be very persistent to succeed. If you think you have the competencies and enthusiasm to get started with these highly rewarding fields, don’t wait. Take some data science and artificial intelligence courses to have an edge over your competition.