How to become a Data Scientist

Data Scientists are some of the most in-demand professionals in the United States. The U.S. Bureau of Labor Statistics places this job at number four on its list of Fastest Growing Occupations, projecting 36% job growth over the next ten years, with more than 20,000 job openings each year. If you’re considering joining this rapidly growing occupation, you’ll want to learn more about the kind of skills required, where to learn them, and what else you can do to make yourself competitive in this field.

Data Scientists are highly sought after and tend to earn salaries that are well above average; however, these individuals are generally well educated, with a strong set of technical skills and solid experience. To work as a Data Scientist, you’ll need to invest time in both learning and gaining experience. It’s also important to understand that learning is a lifelong exercise in this field due to the fact that it continues to evolve at a rapid pace. 

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Steps you can take to become a Data Scientist

Doing some research is a great place to start in your journey toward becoming a Data Scientist. This means learning more about the field of data science in general and getting a better understanding of some specific jobs within it. You can look at free informational websites, review job postings, and talk to professionals who work in this field. Research can help you make sure this is the field for you and can also aid you in thinking about the specific type of data science job you might be interested in, which can guide your educational choices. 

Take a data science class

Education is a critical part of becoming a Data Scientist. You’ll need to learn both technical and non-technical skills:

• Math
• Statistics
• Probability
• Coding 
• Python
• R
• Machine learning
• Cloud computing
• Working with data
• data wrangling 
• visualization
• Communication
• Problem-solving
• Analytical thinking

Some aspiring Data Scientists attend college, pursuing a degree in computer science, data science, statistics, or a related field. College degrees are highly regarded by employers, and degree programs provide a comprehensive education. However, the typical college degree takes four years and costs thousands of dollars each year, which is not a feasible option for many people. A higher-level qualification, such as a Master’s degree, takes even longer.

A bootcamp or certificate course through a tech school like Noble Desktop is another way to learn data science skills. These programs are less expensive than college and usually take under a year to complete. However, they fit in a lot of learning and include extensive hands-on practice, leaving graduates well-prepared to work in the world of data science. Bootcamps and certificate programs have become increasingly popular in recent years as more and more employers lessen their focus on degrees and embrace a skills-based hiring mindset. Many of these programs are offered in multiple formats, providing students with a high level of flexibility. The most common formats are in-person, live online, and on-demand classes. 

In-person data science classes

In-person classes are the traditional way to learn. They tend to be highly engaging, and you can get instant answers to your questions. Because they run in a space dedicated to learning, outside distractions are less likely. Most people also find that in-person classes make it easy to interact with classmates, which can lead to valuable networking relationships. However, in-person classes may not fit in well with a busy schedule since you need to attend at a specific time and will also have to account for a commute.

Live online data science classes

Live online classes are a popular alternative to in-person classes that include real-time interaction but can be taken from the comfort of home. When you learn online, you log in on your computer and interact with your instructor and classmates just as you would in an in-person classroom. No commute is required. Additionally, if you feel uncomfortable with the dynamics of a live classroom, live online learning can be a more comfortable learning option. A disadvantage is that you’ll need to provide your own equipment, and you may have to navigate technical issues by yourself.

On-demand data science classes

A third data science learning option–on-demand classes–offers the highest level of flexibility. These don’t include live instruction. Instead, they are asynchronous and allow you to work at your own pace, choosing when to study and moving at a speed that suits you. You can even pause the lesson, rewind, or fast-forward content if needed. Many on-demand classes do include interaction with your instructor and with other students, but they give you the flexibility to do this on your own schedule.

Gain hands-on data science experience

Learning about data science in the classroom is one thing while applying your skills in the real world is something else. Both are essential to becoming a well-rounded Data Scientist. You can start gaining experience while you’re still in school, for instance, by finding an internship, entering a competition, or working on your own projects. After you graduate, you can continue building experience as you work in professional data science roles, most likely starting with an entry-level position. Depending on where you want to work, you may also need to gain specialized industry experience. For instance, if you want to work in finance, you’ll need to build an understanding of financial concepts such as banking and investments.

Build a professional portfolio

You’ll want to have some practical projects, applications or other materials that you can show to your prospective employers in order to demonstrate that you really do understand data science and its related skills. This is often presented in the form of a professional portfolio that contains data science projects that you have worked on or completed within the context of your professional training. These materials can help ensure that you can rely on your own work to speak for your abilities. These kinds of portfolios are often hosted online and for data scientists, they are often interactive dashboards, algorithms or other practical programs that they have worked on.

Consider a professional data science certification

If you’re serious about a data science career, a professional data analytics certification can be a good investment. Certifications are standardized credentials that you earn by passing an exam. They are an effective way to prove your knowledge and dedication to employers and are associated with higher salaries and a greater likelihood of advancement. Certifications are also a good way to stay up to date on industry practices. There are dozens of different certifications within this field. Some popular ones include Certified Analytics Professional, SAS Certified Data Scientist, and Microsoft Certified Azure Data Scientist Associate. 

Keep learning about data science

The field of data science is constantly changing, and to be successful, you’ll need to continually push yourself to learn and keep up-to-date with changing technology. While this will be an investment of your time, the ever-evolving nature of this field is something that many people love about it because it means that they never get bored.