Is a Data Science Job Hard? Here’s Why You Should Still Consider It

In 2012, Harvard Business Review (HBR) called the data scientist position the “sexiest job of the 21st century.” At the time, the demand for data scientists mostly came from tech firms and startups in Silicon Valley. Over a decade later, more businesses are gearing up to hire data scientists.

Let’s quickly go over the numbers:

• An article by HBR shared that in 2019, job postings for data scientists on the job search site Indeed had risen by 256 percent.
• The US Bureau of Labor Statistics predicts that data science jobs will grow by 36 percent – more than any other field – between 2021 and 2031.

So, what does it take to become a data scientist? And is it a good career path to consider? We sat down with Mark Barbour, Lead Data Science Instructor of tech bootcamp Flatiron School, to learn more about what a data science career could mean for you!

Is a Data Science Job Hard?

Data science combines mathematics, statistics, machine learning, and AI to gather and analyze data. Data scientists then use this data to extract insights that can inform stakeholders in their decision-making.

So, is it hard? The short answer is yes. But it could be very well worth it. As Barbour shares, data scientists end up being some of the most informed people in a company. “When you have a good grasp of advanced academic skills and how data behaves, that makes you powerful. When people see you as the most informed person in a room, you tend to have a lot of responsibilities. It is hard, but you get better and faster at it.”

Drawing from his 12-year experience in IT Consulting, Barbour says good data scientists must have a strong set of technical skills.

“You’re often the most informed on your team. So, you have to have technical skills. A lot of your day-to-day work will be applying technical skills: cleaning up data, looking through it, understanding it, analyzing it, and modeling it.”

According to Barbour, these are the most important technical skills you should have if you aspire to become a data scientist:

• Programming. You need to be able to work with a programming language like Python or R. You need to work with a database language of an SQL flavor. In some cases, you may need to learn how to work with NoSQL.
• Cloud computing. As a data scientist, you must know your way around the cloud. In fact, Barbour advises that you should master at least one cloud platform, whether AWS, Google Cloud Platform, or Azure.
• Statistics, Linear Algebra, and Calculus. “Statistics is really helpful for understanding large, complicated systems, and being able to describe measures of central tendency, measures of spread and basic modeling with it,” shares Barbour. “It’s all about getting more informed about multi-dimensional, complex data sets.”

All that said, Barbour reiterates that a data scientist job is also a very soft skills-driven role that will require you to have efficient project management and decision-making skills.

Data Science Careers You Can Explore

Data scientists can work for any organization that utilizes data – which is just about all industries today. Depending on your experience and interests, you can assume various data-related roles such as data analyst, data scientist, data engineer, and machine learning (ML) engineer.

• Data analyst. This role is an entry-level job for a data scientist. Flatiron School describes data analysts as “the gatekeeper for an organization’s data so stakeholders can understand data and use it to make strategic business decisions.”
• Data scientist. A data scientist gathers, analyzes, and interprets large amounts of structured and unstructured data. They create plans for organizations and help them make data-based business decisions. The role requires expertise in computer science, mathematics, and statistics.
• Data engineer. A data engineer prepares data for analytical and operational uses. They build data pipelines that combine information from various sources.
• Data architect. A data architect is an advanced role in data science that defines procedures, models, and policies used in collecting, organizing, storing, and obtaining company information and data.

“If you’re an aspiring data scientist, you’ll probably be looking more for a data analyst or data engineer role, depending on whether you’re more of a people person or more of a computer person,” Barbour advises.

Can Anyone Become a Data Scientist?

Data science involves expert data analysis to extract valuable insights and create innovative solutions to business problems. That’s why those who have a knack for problem-solving and an interest or experience in programming, statistical and data analysis, and machine learning tend to excel in this field.

“Probably not just anyone [can become a data scientist], but definitely a lot more than people think,” says Barbour. “Learning how to program alone has become much easier in the last 10 years. As a result of that, it’s a lot easier to learn statistics, calculus, and linear algebra when you can use a computer to run through an algorithm to solve a problem. The best advice I can give anybody is to try it out.”

For instance, Barbour says, “You can begin by watching videos online and teaching yourself the basics of data science.” Once you’re ready to commit to more structured and in-depth learning, you should consider intensive skills training programs like Flatiron School’s Data Science Bootcamp.

Become a Data Scientist with Flatiron School

Flatiron School understands that the data science industry changes quickly and, therefore, keeps its finger on the pulse of what the industry currently demands. It offers the Data Science bootcamp, a program that caters to a wide range of backgrounds, from those with computer science degrees to real estate agents.

No matter your background, Flatiron School can help you upskill in no time and prepare you for a data science career. Ready to take the first step? Try Flatiron School’s free data science prep to hit the ground running in the bootcamp!