Top 8 Reasons Why Data Science Jobs Are in Demand

Data science has become an in-demand career field, and companies are increasingly eager to hire experts in this field. In fact, it’s estimated that the data science industry will grow at a rate of 37% per year until 2018, and there will be 1.6 million job openings in the field by 2019 according to Forbes. Whether you’re still deciding if data science would be a good fit for you or have already secured your first data scientist job and are ready to move up the corporate ladder, these top 8 reasons why data science jobs are in demand right now may give you some good food for thought. Data scientist jobs are becoming more and more in demand every year as more industries become digitized and the amount of data continues to grow exponentially with new technologies like the internet of things, machine learning, and artificial intelligence. There’s more opportunity in data science now than ever before. Data scientist job are the new craze that everyone is talking about, but why? There are many factors to consider when deciding whether or not to pursue a data science job, and with so many vacancies in the field, it’s important to know exactly what you’re getting into before committing yourself to one. 

1) There’s No Need To Learn Fortran

Employers are finally catching on to R’s popularity. R is a free, open-source programming language designed specifically for statistical analysis and predictive modeling. It’s a great introduction to data science because it doesn’t require a lot of advanced mathematical knowledge—but by no means does that mean it should be considered an introductory language. By becoming proficient with R, you can work as an analyst or leverage your data science skills when pursuing positions in other industries, such as software development or finance. And you can use R almost anywhere, which means that its popularity is only growing. One study found that 43 percent of companies were planning to implement open source technologies like Hadoop within three years—and every one of those companies plans to use R as well. The field of data science has exploded over the past few years and there’s still plenty of room for growth. So if you have even a basic understanding of statistics, machine learning, or big data applications, then it might be time to start brushing up on your R skills! Even though data scientists spend most of their time writing code (or building tools) to help solve problems rather than analyzing data itself, having an understanding of how different models work will help you better communicate results with business leaders who aren’t necessarily familiar with all aspects of what goes into creating algorithms.

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2) You Don’t Have To Wear a Lab Coat

As with any job, there’s a stereotype of what a data scientist is supposed to look like: white lab coat, pocket protector, and so on. But real-world data scientists don’t look anything like that (or behave anything like Sheldon Cooper). If you want to earn money doing something you love, stop thinking of it as work and start living your dream. You can work from anywhere—like on a tropical island. If you want to make an extra $50k per year—or more—working from home with freelance consulting gigs, then go for it! Master any skill set: Want to become an expert Excel ninja? A Google Apps whiz? Or would you rather master R programming? The world is your oyster. Whatever skills you need to be successful in data science, they’re out there. Get training or get an experience: Maybe you have years of experience under your belt but aren’t sure how to translate that into a career in data science. Maybe you’re fresh out of school and need some pointers on how to kickstart your career. No matter where you’re at right now, we’ve got resources available for everyone who wants to learn more about becoming a data scientist! Use our free self-assessment tool or check out our library of free courses and tutorials. They’ll help you get started on your path toward a new career.

3) You Get To Work With The Newest Technologies

Since data scientist job require workers to know how to handle and use data, it makes sense that you’ll be using all of the newest technologies. And, since companies need people with these skills now more than ever, they’re paying handsomely for them. The median annual wage for a data scientist is $115,900. With such high pay, it seems like no wonder that big companies are clamoring for professionals who have great skills and understanding of working with and analyzing data as part of their day-to-day routine. According to IBM, industries that rely on analytics — marketing research and sales prediction — will employ over a million individuals by 2018. That number is expected to rise to 2.3 million by 2020. That means there’s never been a better time to get into data science! If you’re looking for an interesting career opportunity where your skills can be put to good use immediately, then a data scientist job might just be what you’re looking for. You don’t need a degree: While many positions in data science do require degrees, not all of them do. For example, LinkedIn recently reported that only 36 percent of entry-level data scientists had advanced degrees when they were hired. However, 72 percent had at least some college education under their belts before beginning work as a professional in this field.

4) The Field is Expanding Faster Than Ever Before

According to an infographic by Visual Capitalist, data science-related jobs have risen from 300,000 positions in 2012 to nearly 500,000 today. This is a 53% increase in just three years. Expectations show that growth will continue, too. Research and Markets projects that there will be 1.8 million such jobs by 2020—an astounding 132% increase! For all of these reasons, the demand for data scientists right now is high and it’s only going to go up. Here are some reasons why The field has exploded over the past decade or so thanks to technology continuing to advance rapidly and our ability to capture more information than ever before. More companies need people who can help them store and use large amounts of data intelligently in order to thrive on a digital level—and they’re willing to pay top dollar for those individuals who fit that bill. In fact, job site Indeed reports that 95% of big data job postings specify they must be filled immediately (which isn’t surprising when you consider how quickly things change in today’s business world). While not every position requires advanced degrees or certifications (often times, employers simply want people with solid computer skills), those with extra education on their resumes often command better paychecks as well.

5) Every Company Needs Data Scientists Now

There’s a big gap between people with degrees and skills who can do data science and those who aren’t trained or don’t have skill. Most companies are starting to hire professionals with Master of Science (MS) or Ph.D. degrees in data science, Information technology, computer science, statistics, mathematics or related fields from top universities around the world. As more companies realize that effective data analysis is critical to improving business outcomes across almost every industry, demand for data scientists will continue to grow. Here’s a look at some of biggest reasons why data science jobs are in such high demand right now. Data is king: It seems like everyone wants access to your data these days, whether it’s your company or a competitor. That makes it difficult for businesses to keep up when there isn’t enough time and resources allocated toward analyzing their own data. This need for actionable insights based on real-time information has created an opportunity for skilled data scientists to help make sense of all that information and provide valuable insights into what works and what doesn’t work within an organization.

6) Automation is Getting Better all the time

So-called smart machines and robotics will replace data science jobs just as readily as other office jobs. Of course, for every they’re going to take my job! story out there, you have a situation where automation is creating new opportunities that never existed before. For example, it used to be that having a car was a pretty big deal; now, with Uber and Lyft, thousands of people can make money driving their own cars as part of a fleet. Similarly, data science skills will still be valuable even if someone else has automated your job away. How valuable? According to Payscale, data scientists with less than five years of experience average $89,000 per year. Those who have been at it between five and 10 years earn an average of $123,000 per year. And those who have been doing it more than 10 years bring home an average salary of $150,000 per year.  If learning on your own isn’t really your thing, then consider taking a look at some of these programs: General Assembly: The first program we’ve heard about (though surely not the last) focused specifically on training folks how to use tools like Python, Hadoop and R for analytics.

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7) There’s Plenty of Demand For Professionals Without PhDs

According to Glassdoor, two-thirds of data scientists have bachelor’s degrees or less. The more you know about data science, it turns out, the better off you are. That said, many employers do require at least a master’s degree for entry-level positions and a PhD to move up. But if you don’t have these credentials yet—or can’t even articulate what a data scientist is—don’t worry: There are still plenty of opportunities available for you now. When there’s no clear path forward with your current skill set, take time to develop new ones before jumping ship. You might find that you like where you end up. If you want to work as a data scientist today, keep in mind that education isn’t everything. An academic environment doesn’t necessarily translate into industry experience or vice versa; some professionals get their start as engineers but grow an interest in working with numbers after years spent coding. In fact, according to Indeed Prime Analytics Manager Dragan Gasevicić most companies don’t actually expect candidates to hold specific qualifications. As long as you have basic programming skills, there’s no reason why your career should be stalled by lack of credentials. In addition to building up your technical know-how, it’s also important to develop soft skills for communicating complex ideas in simple terms—and for knowing how and when to ask questions about something you don’t understand. You’ll need these abilities if you’re going to succeed at either of these two common roles: business analyst (who works closely with non-technical teams) or software engineer (who builds tools for other developers). These positions can be good stepping stones toward becoming a full-fledged data scientist.

8) New Jobs are Constantly Opening Up For Data Scientists Everywhere

From banks and credit companies to tech giants like Google, Facebook, Twitter, and Amazon. In fact, according to Linkedin data, some of those jobs may even call for a whopping 7-figure salary for recent graduates. Sounds great right? There’s just one problem… not everyone is qualified for that kind of position. That’s where you come in! If you’re considering making a career out of your passion for numbers and analyzing data; here are eight reasons why you should consider becoming a data scientist 1. Employers love it when their employees love what they do: Employers want people who can’t wait to get up and go to work every day—and most data scientists feel that way about their job. It takes dedication, time, and energy to build up all of your skills as a new employee but once you start seeing real results from your hard work it becomes addictive! Seeing those results could be as simple as using spreadsheets or software tools such as RStudio or SAS or it could mean launching algorithms against thousands of social media posts on Hadoop clusters—but either way, there will be results waiting for you at the end.

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