Want To Become A Data Scientist? Where The Jobs Are And What Employers Are Looking For
Via Forbes : As we consider what parts of the labor market thrived in 2016 and what will continue to gain momentum in 2017, it’s hard to miss the demand for data scientists: people who are, according to SAS, “part mathematician, part computer scientist, and part trend spotter” and “straddle both the business and IT worlds” to analyze complex business problems using large datasets.
In this data-dominated era, everything and everyone produces a digital paper trail. If businesses want to gain an edge, they need to be able to tap into those large, elusive data sets to make better decisions about how products are built, markets are found, clients and employees are supported, and sales are generated. Hence the need for data scientists. It has become crucial to employ analysts who can turn all that raw information into actionable insight—so much so that many positions, ranging from financial analysts and computer systems analysts to statisticians and economists, are increasingly engaged in the art of data science.
According to data produced by Emsi and CareerBuilder, there were, on average, 2,900 unique job postings active per month for data scientists over the past nine months. (NOTE: The total number of job postings is, of course, much higher because employers advertise on many different job sites. Emsi has de-duplicated those postings to the real number of locations / businesses posting ads for those jobs.) The top states for data science job postings are California, Washington, New York, Virginia, and Massachusetts, while the top metros are San Jose, Seattle, New York, Washington, D.C., Chicago, and San Francisco.
Consistent with the digitalization of the labor market, the companies looking for this talent represent virtually every industry. If you want a job at a major, fast-growing company, look no further than data science. Oracle, Microsoft, Amazon, Apple, Booz Allen Hamilton, GE, State Farm, Walmart, Facebook, United Health Care, Aetna, AT&T, Intel, IBM, Nielsen, KPMG, eBay and many more all show up prominently in job postings for data scientists.
So, what does it take to become a data scientist?
If you’re a jobseeker, how might you become a data scientist? If you’re a hiring manager or employer, what are other businesses looking for and what knowledge and skills (or college majors) are producing data scientists?
When we consider the full text of what employers are looking for, we notice an interesting trend. Yes, hard skills are obviously important: analytics, research, machine learning, statistics, Hadoop, and more. But we also see heavy emphasis on many soft skills: the ability to lead, communicate, learn, think critically, work on a team, and be an ethical and reliable worker. In other words, businesses need human data scientists—not robots who process data. They need solid, well-rounded workers with both foundational skills and technical talent. Data scientist is very much a hard-skill career built on a lot of soft skills.
The demand for soft skills is an especially pronounced trend, given our age of booming automation. Even for highly technical jobs, companies need people who demonstrate more than just the ability to crank out analysis. According to recent research from Bruce Tulgan and SHRM, “While it’s well-known that a technological gap of science, technology, engineering, and mathematics skills exists, there is a growing soft skills gap in the workplace.” This notion was also supported at the recent Emsi conference, where the importance of soft skills was mentioned by Emsi clients in nearly every breakout session and best-practice example. Yes, businesses need workers with incredible technical abilities, but they prefer ones with a real heart and soul.
What majors do companies mention in their job postings?
Companies looking to hire data scientists mention majors such as economics, mathematics, statistics, computer science, operations research, and engineering. In 2015 there were 164,000 graduates across these majors—an increase of 5% since 157,000 graduates in 2003. However, the growth in jobs seems to be outpacing the growth in graduates. During the same time period, job growth for these analysis ninjas grew much more: 325,000 new jobs, or 24%. And much of that growth (241,000 jobs) occurred just between 2010 and 2015.
What types of jobs are we talking about?
As was mentioned earlier, the title “data scientist” could apply to a number of occupations. In the list below are 10 examples.
These careers represent over 2.5 million jobs and grew by 12% (or 278,604 new jobs) from 2012 to 2016. Average wages are between $33 and $55 per hour, or $68K and $114K annually. Six of the careers typically require a bachelor’s degree, three a master’s, and one (computer and information research scientists) a doctoral degree.
Computer and information research scientists is the highest-paying job on the list (nearly $55 per hour average). The fastest-growing job is operations research analysts (19% growth). Systems analysts added the most new jobs (80,000), and at nearly 820,000 total employment, management analysts is the largest.
The metros with the highest per capita employment for these 10 positions are San Jose, Washington, D.C., San Francisco, Austin, Charlotte, Boston, Durham, Columbus, and Seattle. Provo, Utah, has seen the fastest growth (37%) with Austin just behind (35%). New York, San Francisco, and Dallas have added the most new jobs since 2012 each contributing over 10,000 in four years.
It’s easy to see why data scientist would be labeled a top career of the 21st century. Despite the growth of the positions above, many sectors continue to feel the pinch for professionals with the education, training, and analytical prowess to turn big data into real insight—making data scientists some of the most sought-after talent in the labor market.
Rob Sentz is the Chief Innovation Officer at Emsi and the founder of Find Your Calling, a free service designed to help students find their ideal career.
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