Late Julian Besag, a noted statistician, was invited to a multi-disciplinary conference at Europe to speak about the future of statistics circa 2003. He was caught off guard by a noted chemist, who commented that statistics was soon going to be obsolete. Increased accuracy of new technologies would, according to the chemist, leave little room for statistical error.
That was then! Today we know that the exact opposite has happened. The new technologies, in fact, have ushered a new era of statistical innovation, due in no small part to the big data boom. While the measurements have gotten more accurate, we are now able to measure more things and new things, needing more statistical applications.
The need for statistics is now realized across a wide variety of disciplines, from industry to government to academia. By providing decision rules and estimation based on exact science, statistics serves a key role in any scientific endeavor. The value of such ability has long been realized in some sectors of industry and academia. Other sectors have recently caught on, creating a high demand for statisticians, along with high salaries.
According to glassdoor.com, the national median salary for data scientists is $115,000 (n=361), and they are employed by a variety of industry leaders: Facebook, Google, Microsoft, Apple, IBM, eBay, Netflix, American Express, MasterCard, Nokia, AstraZeneca, Merck, etc. For comparison, the national median salary for computer scientists is $103,000 (n=845). However, these high salaries and high demand are yet to create enough job seekers with analytical expertise. According to McKinsey Global Institute and McKinsey's Business Technology Office, the U.S. needs 140,000 to 190,000 more people with analytical expertise and 1.5 million manager level experts who can interpret big data analyses. To meet this demand, universities are expanding their statistics and data science programs. There has also been a renewed interest in statistics among students. The number of students graduating with a bachelor's degree in statistics has approximately doubled since 2008, according to the National Center for Education Statistics. However, we are nowhere near meeting the shortage, and it is about to create a big hiring boom for graduates with analytical skills.
The demand for well-trained statisticians is here to stay. This is partly due to the ongoing big data boom, which can only get bigger. Computational methods, being indispensable for big data analyses, are going to be even more important in future. New graduates, who have significant knowledge in statistical computing and data mining technologies, will have an edge.
Another aspect of big data is the multiple layers of data from different types of sources. For example, health related data can be analyzed along with genomic data and social networking data. Recognizing this, National Science Foundation has already started at least one program geared towards combining specific multi-layered datasets. The statisticians with ability to effectively design new analyses combing different types of data will be in high demand.
The Bureau of Labor Statistics has projected a 27 percent increase in statistical jobs from 2012 to 2022. This outlook is far better than the average for all professions. Overall, it is a good time to start your career with a biostatistics degree.
See the results of the Salary Survey confucted by a contractor of the ASA:
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