With the innumerable amounts of data generated in the technology era, data scientists have become an increasingly needed vocation. The US just named its first Chief Data Scientist and all the top companies are hiring their own. Yet due to the novelty of this profession, many are not entirely aware of the many career possibilities that come with being a data scientist. Those in the field can look forward to a promising career and excellent compensation. To learn more about what you can do with a career as a data scientist, checkout this infographic created by Rutgers University’s Online Master of Information.
Data Scientist Career Trends
Persons interested in pursuing a career in this line of work should be prepared to go the distance in terms of their education. If we look at the current crop of data specialists, we will see that nearly half of them have a PhD at 48%. A further 44% have earned their master’s degree while only 8% have a bachelor’s degree. It is clear that a solid academic background will help in immensely both in gaining the knowledge required for this career as well as in impressing the important gatekeepers in various companies.
Getting certified is another good strategy in creating an excellent resume that will draw offers from the best names in the industry. There are four common certifications that are currently available. These are the Certified Analytics Professional (CAP), the Cloudera Certified Professional: Data Scientist (CCP-DS), the EMC: Data Science Associate (EMCDSA), and the SAS Certified Predictive Modeler. Each of these is geared towards specific competencies. Learn more about them to find out the best ones to take for the desired career path.
The explosion of data is a fairly recent phenomenon aided by digital computing and the Internet. Massive amounts of information are now being collected every day and companies are trying to make sense of these. The pioneers have been around for a while but the bulk of the scientists working with data have been on the job for only four years or less at 76%. It’s a good time to enter the field for those who want to be trailblazers in a fresh and exciting area of technology.
There are plenty of issues that are yet to be cleared up with data possibly providing a clear answer once and for all. In this field, practitioners are often relied upon to conduct research on open-ended industry and organization questions. They may also extract large volumes of data from various sources which is a non-trivial task. Then they must clean and remove irrelevant information to make their collections usable.
Once everything has been primed, the scientists then begin their analysis to check for weaknesses, trends and opportunities. The clues are all in their hands. They simply have to look for the markers and make intelligent connections. Those who are into development can create algorithms that will solve problems and build new automation tools. After they have compiled all of their findings, they must then effectively communicate the results to the non-technical members of the management.
Data scientists are well-compensated for their technical skills. Their average earnings will depend on their years of experience in the field. Entry-level workers with less than 5 years under their belt can expected to earn around $92,000 annually. With almost a decade in data analysis, a person can take home $109,000 per year. Experienced scientists with nearly two decades in this career get about $121,000. The most respected pioneers earn $145,000 a year or more. The median salary was found to be $116,840 in 2016.
There are several industries with high demand for data scientists. It should be no surprise that the largest employer is the technology sector with about 41%. This is followed by 13% who work in marketing, 11% in corporate setting, 9% in consulting, 7% in health care, and 6% in financial services. The rest are scattered across government, academia, retail and gaming.
At their chosen workplace, they often take on more than one job role. Around 55.9% act as researchers for their company, mining the data for valuable information. Another common task is business management with 40.2% saying they work in this capacity. Many are asked by their employer to use their skills as developers and creatives at 36.5% and 36.3%.
Career Profile of US Chief Data Scientist
Dr. DJ Patil was an undergrad in Mathematics at the University of California in San Diego before earning his PhD in Applied Mathematics at the University of Maryland. Here he used his skills to improve the numerical weather forecasting by NOAA using their open datasets. He has written numerous publications that highlight the important applications of data science. In fact, he co-coined the term data scientist. His efforts have led to global recognition including an award at the 2014 World Economic Forum. In 2015, he was appointed as the US Chief Data Scientist.
His work experiences have enabled him to use his skills in various industries. For instance, he was the Vice president of Product at RelateIQ, Head of Data Products and Chief Security Officer at LinkedIn, Data Scientist in Residence at Greylock Partners, Director of Strategy at eBay, Assistant Research Scientist at the University of Maryland, and AAAS Policy Fellow at the Department of Defense.
Job Growth and Demand
Projections for this career are rosy with well-known publications hailing it as the next big thing. Glassdoor named it the Top Job in America for 2016. The Harvard Business Review called it the Sexist Job of the 21st Century. The good news for those who are thinking about starting on this path is that there’s plenty of room for new people. Nearly 80% of data scientists report a shortage in their field. They need reinforcement given the volume of work that they have to do. In fact, the projected growth over the next decade is at 11%, which is higher than the 7% estimated growth for all occupations.
According to the experts, interested individuals must do these three things if they wish to succeed in the field: spend time learning effective analytics communication, consider relocation, and interact with other data scientists. The first is crucial as this involves highly technical work with results that need to be understood by non-technical managers. The second is a practical move with 75% of available jobs located on the East and West Coasts. The third is an advice common to all fields: widen your network, learn from your peers, and create future opportunities.
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