Analytics, AIML and Data Science
"The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data."
An analytics professional can ultimately work in a very strategy oriented role or can work as a very specialized deep learning scientist. The former role has a stronger component of business, while the latter role has a much stronger component of analytics. Obviously, your role generally has a trade-off between these two components and you can switch between roles that have different proportions of the two components. The value which you create for yourself is a positively correlated function of business understanding and analytics.
The data scientist role is a position for specialists. You can specialize in different types of skills like speech analytics , text analytics (NLP) , image processing, video processing, medicine simulations, material simulation, etc. Each of these specialist roles are very limited in number and hence the value of such a specialist is immense. This is why we are seeing such a high demand for data scientists these days.