Your Guide to Pursuing a Career in Data Science

Your Guide to Pursuing a Career in Data Science

Whether you’re a young scholar trying to decide which field of study to specialize in or you’re an established professional seeking a new challenge, embarking on a new career path is an exciting endeavor; especially if you’re exploring a field like data science. Exciting, fruitful, and innovative, data science combines various areas of statistics and computation to interpret data and ultimately facilitate decision-making purposes. As businesses increasingly shift their operations to the digital sphere and more industries become intertwined with the technological landscape, understanding data science processes has never been so valuable.

That said, given the broad and ever-changing nature of data-related practices, it can be difficult to know where to start if you’re hoping to get your foot in the door and kick start your career in data science. With that in mind, let’s take a look at some of the key information you’ll want to know.

Careers in Data Science

You may think that pursuing a career in data science means you’ll have to become a data scientist. In reality, however, the field is so broad and multifaceted that there are several professional pathways you can explore. This is largely because data science plays a critical role across most industries. Consider farming, for instance: farmers use data to foster efficient food growth and delivery, while food suppliers use it to minimize food waste, and not-for-profit organizations use it to enhance their fundraising efforts.

The proliferation of data science across various sectors means you not only have your choice of industries to work in, but also the nature of the role you’ll take on. While you can certainly opt to become a data scientist, you can also become a machine learning engineer, a machine learning scientist, a data engineer, a business intelligence (BI) developer, a statistician, among many other roles. While all of these are data-centric professions, the specific responsibilities and duties will vary slightly; for instance, machine learning engineers create data funnels and deliver software solutions, focusing on the design, construction, and maintenance of machine learning systems, while statisticians collect, analyze, and interpret data to identify trends and ultimately inform organizational decision-making.

Educational Pathways

Pursuing a degree in data science is an excellent way to not only familiarize yourself with the industry’s expected trajectory but to hone your skills in relevant disciplines. Institutions all over the world offer programs in data science and other data-centric fields at various postsecondary levels, including undergraduate, graduate certificate and diploma, master’s, and doctorate. You’ll want to consider several criteria when selecting the best university for your chosen career, including the academic course itself, the university’s ranking and accreditation, and its facilities. Be sure to do your research on all of these factors before submitting an application to ensure the school matches your requirements.

If you already have an undergraduate degree, a graduate certificate or a graduate diploma in a relevant field, a master’s degree is a logical next step in heightening your level of expertise and your chances of securing a managerial position within the field. An online Data Science Masters is a great option because of the flexibility it offers; you can study from anywhere, whenever your schedule allows. Additionally, much like on-campus schooling, online education also allows students to gain mastery of the knowledge and skills needed to land them jobs after completing the online course.

Important Resources

When embarking on a new professional journey, it’s important to have the right resources at the ready to ensure your success. When it comes to the field of data science, some of the most essential resources you’ll want to utilize include coding and programming tools (e.g. Python), peer groups, and influential figures’ public platforms. Given that these are the programs you’ll be using on a day-to-day basis in your job, understanding and gaining proficiency in prevalent coding tools is a necessary step in making yourself an effective and desirable candidate. Peer groups also act as a fantastic resource because they allow you to interact and share information with your data science peers, who share similar interests and goals, and will ultimately keep you motivated. Finally, consulting influential data science professionals’ public platforms, such as their social media accounts, is an excellent resource because you’ll remain up to date on the sector’s recent developments and on industry leaders’ initiatives.

If you’re planning to pursue a career in data science, you’ve made an excellent decision; innovative and transformative, data science is a booming industry, with positions in this sector in consistently high demand. In familiarizing yourself with the industries you can become involved in, the roles you can fill, your educational options, and salient resources to consult, you’ll create a strong basis for success and start your new career path on the right foot.

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