Data science is getting bigger, courtesy massive data inflows and the need to extract great insights to guide company operations. Professionals have a number of interesting roles to pick from.
Data is everywhere! Businesses across the world are constantly generating data on various parameters of their work, and this data is often used to extract valuable insights that could guide the future course of action. Data science helps to do this, allowing businesses to understand consumer behavior and accordingly tweak their operations, products, and services, and more. It is no wonder that Max Levchin, co-founder of PayPal, said: “The world is now awash in data and we can see consumers in a lot clearer ways.”
A January 2019 report from job site Indeed showed that the demand for data scientists has grown at a CAGR of 29% from 2013, with an absolute growth of 344%. Similarly, data from technology job site Dice showed the number of data science job postings on its platform – as a proportion of total posted jobs – has increased at a CAGR of about 32%. And, LinkedIn data in 2019 showed that data scientists have a median base salary of $130,000, and saw 56% more job openings this year than in 2018. Data science certainly looks like a great career choice!
However, the Indeed data also revealed that searches by job seekers skilled in data science grew at a slower pace (14%). This suggests that there is a fair gap between the supply of and the demand for data scientists. And therein lies the opportunity! Data science has caught the attention of jobseekers, with fresh graduates striving to get into data science and seasoned professionals putting in efforts to learn and transition to a data science career.
Because there is so much data! The demand for data science spiked almost instantaneously, as companies got their hands on large volumes of data. Although data-driven decision-making has been a key part of operational strategy at successful organizations, it has now become mainstream. Companies can now use this data to understand customers and their behavior, sort out operational challenges, and build better employee retention strategies.
Problems previously solved with guesswork or hit-and-trial methods are now tackled by data analysis – collectively called data science. This combines statistical techniques, programming, and sophisticated machine learning algorithms to dissect problems to their simplest form, and derive solutions. Thus, companies need to hire people skilled in data science.
I bet job-seekers are queuing up!
Certainly. To take advantage of the demand, professionals are moving towards data science certifications, training, workshops, and seminars. They want to put in their best to equip themselves with the required skills.
Contrary to popular belief, ‘data scientist’ is not the only role available in the data science field. There are many other roles, with differences in roles and responsibilities, as well as in technological and other skill requirements. A common career path is a progression from ‘analyst’ to ‘principal data scientist’, and a typical data science team comprises analysts, data scientists, senior data scientists, and principal data scientists, among others.
Some of the common roles in data science are explained below:
The future seems bright!
It is. After all, Tim Berners-Lee, known as the inventor of the World Wide Web, said: “Data is a precious thing and will last longer than the systems themselves.”