1) The United States is Home To More Data Scientists Than Any Other Country

According to a recent study by John Horton of Clearbridge Associates, in 2012 there were an estimated 248,000 data scientists in the United States—more than four times as many as in China. What’s more, those numbers are expected to increase significantly; IDC (International Data Corporation) predicts that by 2018 more than two million people will work directly with big data. This is why learning data science is so valuable. Most companies would benefit from a deeper understanding of how they can analyze and use their own data, and analytics knowledge makes you much more employable. In fact, studies show that 80% of all jobs in 2020 will require some level of digital expertise. The demand for data scientists is growing faster than supply: It’s predicted that most organizations currently lack sufficient data scientists to meet current demand. To make matters worse, these experts aren’t cheap; salaries start at $120k per year and rise rapidly depending on experience level.

 

2) Machine Learning, Cloud Computing, And Deep Learning Are In High Demand

According to LinkedIn, there are around 40 job openings for data scientists for every person with a Ph.D. in statistics. The situation is similar in other industries as well. As Chris Wiggins from TD Bank says: The demand for people who understand data is enormous. We literally do not have enough talent. It’s not easy to find people with expertise; fortunately, now it’s easier than ever to develop your own data science skillset (and earn certification while you’re at it). Even if you don’t want to go into data science full-time, having a solid understanding of how companies use their information can be very valuable. Businesses will always need smart people who can make sense of their numbers and help them grow. The best way to learn data science is through hands-on experience or through attending a certification program. There are plenty of free resources out there – but paid courses offer extra support. Building a personal website/portfolio helps recruiters evaluate your abilities. Online courses give you access to mentorship.

3) There’s An Increasing Need For Professionals Who Can Make Sense Of Unstructured Data

Now generating 2.5 quintillion bytes of data each day and 80% of it is unstructured. Companies across industries need people who can make sense of that data in order to make decisions and drive business outcomes. It’s a booming field, with growth projected at 27% from 2016 through 2026—twice as fast as other IT jobs (McKinsey Global Institute). As such, many businesses are looking for professionals who can do that work in-house, but there isn’t a centralized source for learning more about data science: it’s not taught widely at universities, nor is there a list of best practices on how to build a career in data science. There’s definitely an opportunity here if you’re looking to get into one of the hottest fields around!

4) IT Companies Are Hiring Many People With Data Science Skills

The need for skilled data scientists and experts is increasing, as many businesses are now trying to collect and analyze data in order to improve their business performance. Many IT companies now hire people with strong data science skills and provide them with proper training. According to recent reports, there are more than 100,000 job openings available for data scientists in India alone. The salaries of data scientists are also quite high in comparison to other IT professionals. If you want to pursue a career in data science, it’s important that you keep yourself updated about the latest trends and get a certification course in this field. Data Scientist has been ranked as one of the best jobs in America: A survey revealed that Data Scientist has been ranked as one of the best jobs in America. This particular profession was ranked first among all jobs based on salary and fourth based on overall satisfaction level among employees. The median base salary for a person holding a position as a data scientist is $110,000 per year.

5) Data Science Skills Are In High Demand

A recent study conducted by data science hiring platform Profoundis found that 94% of businesses are looking to fill open positions in data science and analytics. According to McKinsey, organizations that have incorporated big data have enjoyed a 15% increase in profitability. The digital world has opened up a lot of doors for companies, but it’s only with tools like data science that they can actually achieve high returns on their investments. With high demand and big rewards, it’s no wonder everyone wants to be a part of what seems like an exciting new field with unlimited potential. But how do you break into data science? What skills do you need? And where do you start? There isn’t just one way to enter data science—the industry is filled with different subfields that each cover different areas of expertise. Some common subfields include business intelligence (which analyzes customer behavior), statistical analysis (which uses statistics and mathematics to interpret large datasets), predictive analytics (which applies mathematical modeling to predict future outcomes), and machine learning (which utilizes algorithms in order to automate decision-making). However, there are many other subfields too!

6) Companies Hire About 16 Percent Of Applicants With Data Science Skills

According to one report, only 16 percent of applicants with these skills are hired by employers. The same report notes that it takes most data scientists 3-6 months to land their first position. To avoid these job hunting woes, consider enrolling in a training program or pursuing any certification program. Many universities also offer dedicated programs in data science that could bring about new opportunities after graduation. Companies pay around $116,000 per year: On average, companies pay roughly $116,000 per year for data scientists. That’s a big difference from average salaries elsewhere in IT—like web development and programming—which tend to be around $80k annually. That’s not all: Pay varies wildly depending on industry and experience level. Entry-level data scientists earn closer to $90k while those who have been at it longer can make as much as $150k+.

7) Some Companies Specialize In Artificial Intelligence Projects

Artificial intelligence (AI) has a long history and it is constantly making progress. The AI we know today was created in 1956 when two men, John McCarthy, and Marvin Minsky, published a paper detailing their work on how computers could be taught to play checkers using a technique called recursive search algorithms. The algorithm essentially means that if your computer opponent is smarter than you at checkers, then you will take turns playing against each other until one of you wins. In theory, it sounds easy enough for a computer to beat us at checkers since there are billions of moves possible in every given situation. Still, many years later, no one has been able to create an artificial intelligence program capable of beating top humans at competitive games like chess or go.

8) Qualifications Vary Widely Among Positions In This Field

One of the more interesting things about data science is that job requirements vary widely depending on where you are. Some jobs only require a bachelor’s degree, while others demand years of experience with specific software. Some even require applicants to be familiar with natural language processing tools like Python or R. Take a look at some jobs to see what skills are required in your area.  Another way in which qualifications differ from one industry to another is whether there’s any need for an advanced degree. In most cases, employers aren’t looking for candidates who have specialized degrees—at least not right away. Employers expect entry-level candidates to have a Bachelor’s Degree and an understanding of statistics and mathematics and usually don’t need anything else beyond that for starting positions. If you got any training in this field it will add more to your job hunting procedure.

9) Big Data Skills Are Highly Sought After

The internet is a huge source of information. The average person who visits social networking sites like Facebook, YouTube, and Twitter generates more than 1.8 gigabytes of data per day—that’s more than 80 million times as much data in a single day as was stored on all computers worldwide in 1986, according to IBM. Much of that data is extremely personal—including everything from buying habits to relationship status to location. Naturally, all that data is worth money—and it’s driving demand for people with big-data skills.

 

10) The Median Salary For a Typical Data Scientist Is $107,000.

The mean, on the other hand, is $118,000. If you’re working at one of these companies and have a pulse, expect a raise in 2014! (Glassdoor)#1: The Average Salary for a Data Scientist Is Not $120K!: There are several factors that go into determining your actual salary as a data scientist. One is your skillset—it’s much easier to secure top dollar if you can show proficiency in Python or SQL (or both). Another key factor is experience; an average salary for an entry-level data scientist might be closer to $70-$80K. Data Scientists Don’t Get Paid That Much More Than Other IT Professionals. According to Glassdoor, A Typical Entry Level Position Would Pay Around $60K/Year.

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