Rapid advancements in computer processing technology are enabling government, businesses, and individuals to generate more data than ever. And as this data grows to record levels on a daily basis, experts say the role of data scientist will be one of the fastest-growing professions in the coming years.

A report from IBM Marketing Cloud said 90 percent of the world’s data was generated in the past two years alone and more than 2.5 quintillion bytes of data is now generated per year.

IBM said demand for data scientists will rise by more than 28 percent between now and 2020 when there will be more than 2.7 million people working in the field. These advertised data scientist jobs pay an annual average salary of $105,000, and often more for candidates with a few years of experience.

The report said the transformative powers of data is creating a growing "demand for a new breed of processionals skilled in data, analytics, machine learning and artificial intelligence."

IBM's study found recruiting for these jobs can be difficult, and the high cost to hire, the need for new training programs and the high risk to future productivity is one of the greatest challenges organizations will face in their data science initiatives.

Many students are entering the profession, and data scientists now are working in virtually every industry from healthcare and insurance to advertising and entertainment.

While the specific roles of data scientists can vary, their general duty is to gather and analyze data to provide more value to the organization. Most data scientists spend their days building and engineering machine learning programs and models while applying advanced statistics and mathematics.

Despite growth in the industry and the opportunity it presents for workers, there is no direct or agreed upon career path. Vivian Zhang, founder and CTO of the NYC Data Science Academy and an adjunct professor at Stony Brook University, says data scientists can come from many industries.

Many have a master’s degrees or Ph.D. in a quantitative field such as physics, computer science, mathematics or statistics. Others have relevant work experience in analysis in their respective fields.

One thing most data scientists have in common is a background in math and basic programming languages such as C++, Java or Python. Most also have a certain specialty and attend online courses or boot camps to become proficient in things like data mining, data analysis and machine learning.

"There are constant debates about how to become a data scientist … No matter how you decide to proceed, you must learn some skills one way or another in order to get hired and have a successful career," Zhang said.