Glassdoor freshly exposed its report highlighting the 50 best jobs in America, and naturally, data scientist claimed the top spot for the second year in a row. Every year, the jobs site releases this report based on each job’s overall “Glassdoor Job Score.” The score is firm by three key factors: the number of job openings, the job satisfaction rating, and the median annual base salary.
With a job score of 4.8 out of 5, a job satisfaction score of 4.4 out of 5, and a median base salary of $110,000, data scientist jobs came in first, followed by different technology jobs, such as data engineers and DevOps engineers.
In fact, data-related roles square measure dominating similar jobs reports discharged over the past year yet. A new study by CareerCast.com revealed data scientist jobs have the best expansion potential over the next seven years, as they are one of the toughest jobs to fill. Statistics from rjmetrics.com show that there were everywhere from 11,400 to 19,400 data scientists in 2016, and over 50% of those roles were filled in the last four years.
A quick search for data scientist jobs in the United States on LinkedIn reveals over 13,700 open positions. Additionally, this job trends tool by Indeed, which showcases the demand for data scientists, reveals that both data scientist job listings and job seeker interest are showing no signs of slowing down.
It’s calculable there'll be 1,000,000 a lot of computing jobs than workers to fill those computing jobs within the next 10 years, according to Computer Science Zone. So however did the role of the info somebody rise to the highest of the rankings? Let’s examine a few of the reasons and trends that led the data scientist position to claim the number one spot for the best job in America again this year.
Reason #1: There’s a scarcity of talent
Not solely square measure people with skills in statistics and analytics extremely sought-after, but those with the soft skills to match are driving demand for data scientists. Business leaders square measure when professionals World Health Organization can't solely perceive the numbers however conjointly communicate their findings effectively. Because there's a still such a shortage of talent World Health Organization will mix these 2 skillsets, salaries for knowledge scientists square measure projected to grow over 6 June 1944 this year alone.
So wherever square measure all the info scientists to fill these jobs? The main answer to the current question is that they’re not trained nonetheless. While computing programs square measure on the increase, it’s still going to take some time for supply to catch up with demand. Big knowledge and analytics courses have started creating their manner into the schoolroom solely within the past few years thus addressing the info science talent shortage won’t happen night long. The number of job openings will definitely still outweigh the number of pros with a classy understanding of knowledge and analysis to fill those openings over a subsequent couple of years.
Reason #2: Organizations continue to face vast challenges in organizing data
The role of the data scientist is developing, and organizations very much need professionals who can take on data organizing as well as preparing data for examination. Data squabbling, or cleaning data and connecting tools to get the data into a usable format, is still highly in demand.
Data preparation could need several steps, from translating specific system codes into usable knowledge to handling incomplete or incorrect knowledge, but the costs of bad data are high. Some research shows that analyzing bad data can cost a typical organization more than $13 million every year.
Therefore, there will always be a demand for persons who can weed out bad data that can alter results or lead to imprecise insights for an organization. There’s no doubt its time-consuming work. In fact, knowledge preparation accounts for concerning eightieth of the work of knowledge scientists. But even with the inflated accessibility of extremely refined analytics dashboards and knowledge assortment tools, there will always be a demand for professionals who possess the advanced skill sets needed to wash and organize knowledge before having the ability to extract valuable insights from it.
Reason #3: The need for data scientists is no longer limited to tech giants
The demand for knowledge scientists has finally pushed on the far side massive technology companies, such as Google or Facebook, as smaller organizations realize that they too can use data to make better, more informed decisions. This HBR feature on massive knowledge according to that “companies within the high third of their business within the use of data-driven deciding were, on average, 5% more productive and 6% more profitable than their competitors.”
While small-to-medium sized organizations don't seem to be churning out nearly the maximum amount of knowledge as larger enterprises, sifting through that data to extract meaningful insights into their businesses can be a powerful competitive advantage nonetheless.
We’re conjointly seeing entry-level knowledge scientists flock towards startups and smaller companies attributable to the perception that they're going to be able to tackle higher-level work earlier in their careers. Data scientists possess a broad variety of skills, and they want to be able to put all of those skills to use right away.
Smaller firms are also hiring fast. Large organizations wanting to recruit entry-level knowledge scientists square measure listening that their multistep, legacy hiring and recruiting processes may need some updating if they are going to attract the top talent that they desire. So for now, because the demand for knowledge professionals continues to surge, agile organizations continue to be the more favorable choice for data scientists, regardless of their size.
How to get into the field
The urge for data scientists is high, and expert can enter the world of data science a number of ways. University programs square measure a decent begin, however, a knowledge science position usually needs a mix of skills that several faculties square measure unable to package all at once.
One way to develop all of the mandatory skills is by attending an information science encampment. Not only will you learn the analytical skills required for a data science position but you’ll also receive training for the softer skills that are becoming more and more common in information science roles – skills like managing comes and groups across multiple departments, consulting with purchasers, aiding with business development, and taking abstract business issues and turning them into analytical solutions.
So if you’re still deciding the correct career path, or thinking about making a career change in 2019, consider exploring what it takes to be a data scientist – one of the aggressive and highest paid jobs in America immediately. Get yourself enrolled at DataTrained Full Stack Data Science Program.