Named “the sexiest job of the 21st century” by the Harvard Business Review in 2012, Mashable’s hottest profession of 2015, and Glassdoor’s most popular job 2016, data scientists are the just broaching the frontier of what’s possible. While still in its infancy, this young profession has exploded in popularity and need. Entire disciplines and areas of business have been born of the need to glean insights from vast amounts of, otherwise, indecipherable information. Data scientists emerged to meet this growing need – to bring structure to large quantities of formless data and to glean actionable insights.
Data scientists are utilizing ever more sophisticated programs and harnessing the increasing power of computers to structure data that was previously unstructured and apply methodological rigor on data sets that are increasing in size.
The rate of data growth in the digital universe is expanding exponentially. One study estimates that by 2020 the amount of data globally will grow ten-fold from today. However, all this data isn’t worth anything unless it can be compiled, sorted, analyzed, and manipulated. Data in its raw form is nothing but numbers in a spreadsheet; untapped potential.
So, what exactly does a data scientist do? What skills are necessary to excel in the profession? And, what sets this profession apart from the more established mathematicians and statisticians?
Data scientists are analysts, explorers, individuals with a passion for doing good things with data. They aim to find connections between two variables that might be indecipherable and have no correlation to the naked eye. Data scientists are reinventing the wheel and coming up with new approaches to old challenges. They find solutions to vexing problems and new opportunities where one might not think to look.
To achieve these outcomes, they utilize the scientific method. The ability to form a concrete hypothesis, outline a credible plan towards a solution, and assess their own performance throughout are all vital skills data scientists must possess. They write code, develop algorithms, and glean actionable insights.
But perhaps most importantly, data scientists must be effective communicators and passionate advocates. They must be thinking and communicating like businesspeople. Within any organization, data scientists need to help shift the pendulum and ensure that a company’s most senior executives understand and implement their findings.
These are not exactly traits that a majority of college graduates own. In fact, there is a shortage of qualified scientists to fill the growing demand. That’s why students with Master’s degrees or PhDs in fields from a host of fields like physics, engineering, and applied mathematics with no work experience often come out of graduate school and receive six-figure salaries to work at companies like Experian, where they undergo further training to become data scientists.
The demand for data scientists is as high as it is because there is virtually no market or sector that doesn’t need one. Businesses certainly understand the power of data sciences.
Recent research by Accenture shows that 87 percent of companies understand the value that data scientists can bring to enterprise.
The realm of data science extends far and wide. In academia, data scientists are helping social scientists to understand how a host of variables impact major international issues like war and terrorism, and are proposing solutions to policy makers. Data scientists assist disaster relief organizations respond to humanitarian crises most effectively and NASA scientists to understand the universe.
In the business world, data scientists can help companies understand risk around financial transactions, detect fraud, optimize marketing to consumers, and help businesses improve digital customer user experiences.
At Experian, data scientists help financial institutions, healthcare organizations, automotive companies, retailers and others make more informed and effective decisions. For example, Data Labs scientists analyzed billions of credit and debit card transactions to understand how population segments spent money. With this information, credit card companies were able to market their products to specific population segments and make rewards programs more attractive to consumers in the process.
Because data science is in its infancy, there’s tremendous room for innovation. Experian’s DataLabs works to assemble individuals from a host of backgrounds with a variety of experiences and encourages them to push the envelope of what’s possible. They look at problems and find solutions that are good for businesses, consumers and society.
As an example, small businesses – the classification of businesses that create nearly two-thirds of net new jobs in the United States – notoriously struggle to obtain loans to grow because of a perceived lack of data on their credit worthiness. Without access to credit, these businesses aren’t able to grow further, preventing them from hiring more people. DataLabs’ latest experiment concerned whether social media sites can help businesses obtain credit.
Right now, the potential of big data is seemingly limitless. Today’s data scientists are the pioneers who will push boundaries and use data to make businesses smarter, more effective and more appealing to their audiences.
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