One of the biggest differences between successful and unsuccessful companies is how well they use data. There has been a massive shift in recent decades towards analytics and data-driven solutions, which has made data science one of the largest “make or break” factors in the success or failure of modern-day organizations.

As a result, the data science industry is booming — offering thousands of new careers each year for analysts looking for positions mining, analyzing and identifying trends in corporate data sets. Positions for data scientists alone are expected to grow 36% through 2031, creating an estimated 13,500 new job openings each year.

Careers in data science: what to know

Not everyone understands or appreciates how genuinely fun, interesting and rewarding data science careers can be. Data science is an ever-evolving field and constantly expanding industry, one that has become essential for organizations who want to become and remain successful.

Nowadays, all businesses — big or small, and in all industries — require at least one person (if not a whole team of people) who can deconstruct, comprehend, organize and use data. Without a proper strategy for managing data, organizations run the risk of becoming obsolete due to their inability to successfully and sustainably collect, analyze and store data.

More than ever, companies need data science professionals.

Deciding to pursue a career in data science is a powerful move for your future, and not just because the average salary is more than $100,000.

In addition to a robust payoff, additional benefits of being a data scientist include:

  • Strengthened communication and interpersonal skills
  • Holding an invaluable, chronically in-demand position
  • Working with big brands (potentially traveling as well)
  • Remote work availability, which has become very popular in the data science world
  • Countless opportunities for career growth and advancement

Now that you’ve reaffirmed exactly why you want to pursue a career in data science, it’s time to identify the potential pattern of your career path within the industry.

What does a data science career path look like?

Data science is a multidisciplinary, diverse field that creates a wide range of career options.

Depending on where you’re starting and which sector of data science you’re planning to pursue, your career path might look different than other aspiring data professionals.

Like other career fields, there are typically four levels of data science roles: entry-level, intermediate, advanced and senior.

Entry-level positions in data science include jobs such as Junior Data Analysts, Junior Data Scientists, Junior Business Analysts and Junior Software Developers.

From there, you would advance to the intermediate level of data science careers, which often include positions like Data Analysts, Data Scientists, Business Analysts and Data Engineers.

More advanced data science careers are reserved for professionals with at least a few years of experience in the field. These careers typically include Data Engineers, Data Architects and Database Engineers.

The most senior-level data science careers include Data Scientist, Senior Data Scientist and Director of Analytics positions.

How do I start a career in data science?

With the right combination of data science skills and education, you can position yourself for the data science position you deserve. Evaluate your career goals, become familiar with the industry and acquire the necessary education to get your start in data science.

1. Evaluate your career goals

First, you need to clearly identify what you’re looking for in a career, the goals you’re hoping to achieve and the skills and strengths you’ll need to get there. It’s easy to romanticize certain industries (especially when they pay a handsome salary), but you don’t want to invest a significant amount of time, energy and resources into a career you won’t enjoy.

2. Become familiar with the industry

Obtaining a career in data science also means taking the time to become familiar with the industry itself.; Spend time getting to know the tools, the resources, the subject matter experts and other features of the data science landscape.

Read books written by data scientists, listen to training sessions or public discussions from experts, network with peers and study the latest-and-greatest trends and techniques.

3. Acquire the necessary education

There are two primary schools of thought when it comes to acquiring the necessary education, skills and training for careers in data science: the first believes a college education is necessary, and the second doesn’t. The truth is, both are correct.

Fewer people are attending college every year for a variety of reasons (cost being a large factor), and more employers are realizing there are many people who possess the skills and intelligence to succeed, but simply lack the technical degree. That’s where bootcamps come in.

4. Invest in a data science bootcamp

A data science bootcamp equips you with all of the important data science skills you’ll need to succeed in the twenty-first century, all without the need for traditional schooling. The best data science bootcamps are significantly shorter than a traditional college degree, at a fraction of the cost.

Pace’s Data Science Bootcamp provides on-the-job experience that rivals acclaimed college learning. You’ll learn industry basics, build or refine the most important hard and soft skills in data science and receive personalized training to help you every step of the way.

Get started in data science today

Pace specializes in equipping aspiring data science professionals with the knowledge, skills and experience they need to succeed in the rapidly evolving, technology-driven data science world.

Whether you’re about to graduate college and start building a career for the first time, or you’re going through a career change after 10+ years, we’re here to help.

Connect with a member of our Admissions team today to get started.