How To Become a Data Scientist in 8 Steps

Data scientists work in multiple fields. These jobs are in high demand, and the average data scientist salary is over $100,000.

To become a data scientist, you'll usually need at least a bachelor's degree. So, what can you do with a data science degree? Keep reading to learn more about how to become a data scientist and how this degree applies in the data science field.

What Is Data Science?

To put it simply, data science is a field that deals with the science of data. However, the field itself isn't simple; it's multi-faceted and includes various aspects of gathering, organizing, storing, analyzing, and communicating data.

Additionally, data science is heavily rooted in computer science and information technology, as data scientists often build and manage the data systems and data warehouses used to process datasets. Data science is used in many fields, including business, finance, healthcare, and more.

How To Become a Data Scientist

To become a data scientist, you'll typically need to earn a degree and gain the skills necessary for success in the data science field. We've broken down the different steps below.

Step 1: Understand the Role

According to the U.S. Bureau of Labor Statistics, data scientists use analytical tools and techniques to extract meaningful insights from data. Their job duties often include:

• collecting data
• determining which data is useful to their project
• categorizing and analyzing data, also called data mining
• creating visual representations of data for communication purposes
• developing and maintaining algorithms and predictive models

Many data scientists specialize in a particular area of the field, such as:

• artificial intelligence and machine learning
• business analytics
• cloud computing
• cybersecurity
• data engineering

Step 2: Earn Your Bachelor's Degree

Most employers require data scientists to have a bachelor's degree in data science or a related field (e.g., data analytics or computer science). Bachelor's degrees are undergraduate degrees that usually take four years of full-time study.

These data science programs usually cover fundamentals such as:

• artificial intelligence and machine learning
• big data management
• data mining
• data visualization
• predictive modeling and deep learning
• programming languages

If you choose a specialization within your degree, you'll also take courses specifically focused on that area of data science. Additionally, data science degrees usually include several math courses in areas like linear algebra and probability and statistics.

Learn more: Is a Data Science Degree Right for Me?

Step 3: Develop Technical Skills

As you progress through your degree programs, you'll develop core skills that all data scientists need to thrive in the field. These data science skills include:

Programming

Programming is an important skill that data scientists need, as they use it in everything from data collection to organization and storage to analysis to visualization. Some of the most common programming languages in the data science field are Python, R, and SQL. Additional courses in languages like Java and Javascript may also be offered.

Data Analysis and Statistics

In data science, statistics and data analysis are intertwined. Statistics is used to create statistical and predictive models needed for data analysis.

Machine Learning

Data scientists use machine learning in many areas of the field. Your program will help you develop a machine learning skill set in topics like regression, neural networks, and predictive modeling.

Data Visualization Tools

Data visualization tools are what data scientists use to break down their data into an easy-to-understand format, like graphs or charts. Common data visualization tools include Tableau and Power BI.

In addition to technical skills, your program will help you develop soft skills like decision-making, problem-solving, and communication skills. You'll also get used to using popular industry software and systems like Hadoop, Pandas, and Spark.

Step 4: Gain Practical Experience

When you start looking for data science jobs, it helps to have practical experience in the field. A great way to do this is through internships.

Some colleges and universities include internships as part of the degree program, while others offer supplemental internship opportunities. These give you hands-on experience in the field and you may even be able to intern for potential employers.

Step 5: Network and Connect

In many industries, including data science, networking and connecting with other professionals is one of the best ways to further your career path and have an edge in the job market.

Internships are one way to start networking, but there are other ways to meet professionals as well. Consider attending seminars or conventions aimed at data scientists or connecting with others in the field on sites like LinkedIn.

Step 6: Apply for Jobs

Applying for jobs can be challenging, but luckily, data scientist jobs are in high demand. The U.S. Bureau of Labor Statistics estimates jobs for data scientists will increase by 36% over the next decade.

When navigating the job market, there are a few things you can do to ease the process. We've listed these tips below.

Tailor Resume and Prepare for Interviews

When applying for a data scientist role, ensure your resume showcases your data science education and experience. Review your resume to ensure this is front and center, and tailor it to the job posting you're applying for.

If you know you get nervous in interviews, bring in a friend to help you prepare. Have them ask you common interview questions so you can prepare your answers ahead of time.

Consider Entry-Level Positions

Some data science jobs require you to gain experience and work your way up. You may need to start by applying for entry-level jobs first.

In many cases, these jobs will have ''junior'' or ''entry-level'' in the job title. For example, a junior data scientist or an entry-level data analyst.

Step 7: Continue Learning and Advancing

Technology is constantly changing, which means people who work in data science must stay up-to-date to do their jobs well. Below, we've highlighted a few ways you can continue to advance as a data scientist.

Pursue Advanced Certifications

Certifications are offered through colleges and universities, as well as online learning platforms like Coursera. They're often online courses, though they are sometimes in-person courses.

These types of programs allow you to advance your knowledge in a specific field of data science. For example, you can pursue a certificate in business analytics or machine learning.

Data Science Bootcamps

Data science bootcamps are similar to certificate programs. They are usually offered online and generally take a few months to complete.

Like certificate programs, bootcamps can help you learn more about a specific area of data science. They can also help you learn specific tools, software, or programming languages.

Step 8: Consider Earning a Master's Degree

While not always necessary, employers often prefer candidates with a master's degree. Master's degrees vary in length, but usually average two years.

Traditional and online master's degree in data science are designed to fine-tune your data science knowledge and skill set. They often offer concentrations so you can focus your learning on your career goals.

Start Your Data Science Career Today

If you're interested in a career in data science, check out the data science programs on Learn.org. Reach out to individual colleges to start your data science career today.