Glassdoor recently revealed its report highlighting the 50 Best Jobs in America, and unsurprisingly, the data scientist took home the top spot for the second year in a row. Each year, the job board publishes this report based on the overall “Glassdoor Job Score” for each job. The score is determined by three key factors: number of job offers, job satisfaction rating, and median annual base salary.
With a 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 first, followed by other tech jobs, such as data engineers and DevOps engineers.
In fact, data-related roles also dominate similar job reports in the past year. A new study from CareerCast.com has found that data scientist jobs have the greatest growth potential over the next seven years, as they are one of the toughest jobs to fill. Statistics from rjmetrics.com show that there were between 11,400 and 19,400 data scientists in 2015, and more than 50% of those positions have been filled in the past 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 from Indeed, which outlines the demand for data scientists, reveals that job postings for data scientists and interest from job seekers show no signs of slowing down.
It is estimated that there will be one million more IT jobs than people to fill those IT jobs over the next ten years, according to Computer Science Zone. So how did the role of data scientist rise to the top of the rankings? Let’s take a look at some of the reasons and trends that led to the job of data scientist claiming the top spot for the best job in America again this year.
Reason #1: There is a talent shortage
Not only are people with statistical and analytical skills in high demand, but those with the necessary soft skills are driving the demand for data scientists. Business leaders are looking for professionals who can not only understand the numbers, but also communicate their findings effectively. Because there is still such a shortage of talent who can combine these two skills, salaries for data scientists are expected to increase by more than 6% this year alone.
So where are all the data scientists to fill these positions? The main answer to this question is that they are not yet formed. While computer programs are on the rise, it will still take some time for supply to catch up with demand. Big data and analytics courses have only started making their way into classrooms in the past couple of years. Therefore, the data science talent shortage will not happen overnight. The number of job openings will certainly continue to outweigh the number of professionals with a sophisticated understanding of data and analytics to fill these openings over the next two years.
Reason #2: Organizations continue to face huge challenges in organizing data
The role of the data scientist is evolving, and organizations desperately need professionals who can support the organization of data as well as the preparation of data for analysis. Data processing, or cleaning the data and connecting the tools to get the data into a usable format, is always in high demand.
Preparing data can take many steps, from translating specific system code into usable data to dealing with incomplete or erroneous data, but the costs of bad data are high. Some research shows that analyzing bad data can cost a typical organization more than $13 million per year.
Therefore, there will always be a demand for people who can weed out bad data that can distort results or lead to inaccurate information for an organization. There is no doubt that this is time-consuming work. In fact, data preparation is about 80% of the work of data scientists. But even with the increased availability of analytical dashboards and highly sophisticated data collection tools, there will always be a demand for professionals with the advanced skills needed to clean and organize data before it can be extracted from it. valuable information.
Reason #3: The need for data scientists is no longer limited to tech giants
The demand for data scientists has finally overtaken big tech companies, such as Google or Facebook, as smaller organizations realize that they too can use data to make better, more informed decisions. This HBR big data feature reported that “companies in the top third of their industry in using data-driven decision-making were, on average, 5% more productive and 6% more profitable than their competitors.”
Although small and medium-sized businesses do not produce as much data as large enterprises, sifting through that data to extract meaningful insights into their business can still be a powerful competitive advantage.
We’re also seeing entry-level data scientists flock to startups and small businesses because of the perception that they’ll be able to tackle higher-level work earlier in their careers. Data scientists have a wide range of skills and they want to be able to put all those skills to use right away.
Small businesses are also hiring quickly. Large organizations looking to recruit entry-level data scientists are taking note that their traditional multi-step hiring and recruiting processes may need an update if they want to attract the top talent they want. So, for now, as the demand for data professionals continues to grow, agile organizations continue to be the most favorable choice for data scientists, regardless of size.
How to enter the field
The demand for data scientists is high, and professionals can enter the world of data science in several ways. College programs are a great start, but a data science position often requires a mix of skills that many schools aren’t able to pull together.
One way to develop all the necessary skills is to attend a data science boot camp. Not only will you learn the analytical skills required for a data science job, but you will also receive training for the soft skills that are becoming increasingly common in data science roles – skills such as project management and of teams across multiple departments, consulting with clients, assisting with business development and taking abstract business problems and turning them into analytical solutions.
So if you’re still deciding on the right career path or considering a career change in 2017, consider exploring what it takes to be a data scientist – one of the fastest growing jobs and highest earning in America right now.