Ongoing Education: A New Imperative for Data Scientists
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Forbes magazine recently dubbed Data Science, “The Century’s Hottest Career”. Companies in every industry, from consumer packaged goods to health care, around the globe are drowning in data and need people who can make meaningful sense of it all. No doubt, there is a strong and growing opportunity for careers in the field. But given the pace of change and innovation – success over the next decade (and beyond) is going to require that data science professionals invest in ongoing education.
In the not too distant past being a data scientist only really required math and statistics capabilities. Today a quick glance at online job advertisements makes clear the biggest demand is for a new combination of skills ranging from data engineer to statistician to business analyst. Organizations don’t just need data scientists – they need highly skilled professionals who are trained to work with modern tools and can identify appropriate methods and models and design human-friendly interfaces. In other words, data scientists have become a hybrid position of several jobs rolled into one.
That’s where ongoing education comes in. The reality is, the field is changing rapidly and new technologies and methods are being developed which are much different than those learned during a college degree or even standard on the job training. Data science is morphing into a multidisciplinary field with elements of data science, information and decision systems, and social sciences as well as connections to engineering domains. Professionals who remain in the field will need to further hone their abilities if they want to remain competitive and take advantage of the ample opportunity now presenting itself. To do so, they will not only need to increase their data analysis skills, but also learn emerging analytics techniques, such as deep learning and its impacts; understand how to overcome the challenges and constraints associated with scaling big data algorithms; and develop a better understanding of how machine learning works in practice. What’s more, data scientists will need to gain knowledge of issues and challenges faced in a wide range of industries outside their specific area of expertise which will enable them to draw insights that could have been invisible without this outside knowledge.
To address this challenge, a good approach is to take advantage of the various professional education options like online courses and nearby conferences. The most successful are those that combine interdisciplinary efforts in a rigorous way. Many of these courses and workshops can be accessed on-demand or via recordings, and require minimal time commitment, yet can help data scientists obtain the competencies required for their new role as they become more and more central to success in business.
Companies of all sorts are in the market for data science professionals, just look at ODSC’s Job board… or click on the “Jobs” tab on the LinkedIn web site, enter the term “data scientist,” search the entire U.S. and, as of mid-January, you’ll find more than 8,600 available jobs. These companies all want to be able to extract real business value from the troves of big data now at their disposal. But for data scientists to deliver on that promise and advantage of the tremendous opportunity that lies ahead, they must continue to evolve and deepen their knowledge. People, organizations and things will continue to generate ever-larger volumes of data in the months and years ahead. Equipping more people with the right tools and training to turn data into insights will allow them not only meet the market need but allow data science to live up to it’s potential.