How to Become a Data Scientist

Written by Coursera Staff • Updated on

Data scientists are among the top jobs in the US. Learn how to become one with this guide.

[Featured Image] A person with curly hair and a pale blue shirt takes a course on how to become a data scientist.

Data scientists bring enormous value to companies by harnessing the power of data and using it to make predictions and draw actionable insights. Between 2022 and 2032, the US Bureau of Labor Statistics (BLS) projects data scientist jobs to grow by 35 percent. This figure represents an average of 17,700 job openings annually [1]. Data scientists also earn higher-than-average salaries and generally feel satisfied with their work-life balance [2].

In this article, we'll discuss how to become a data scientist—with little to no experience—and key skills and technologies you'll want to learn to succeed in this career path.

How long does it take to become a data scientist?

The amount of time it takes to become a data scientist depends on your previous experience, education, and skills. If you're transitioning into data science from a related career such as software engineering or machine learning, gaining the required competencies through certificate programs or online classes may only take a few months.

However, if you do not have a background in data and wish to pursue a data science career, you may need to earn at least a bachelor's degree or gain foundational knowledge and experience in the field through certificates and training to pursue this career. Entry-level data scientists are often expected to know SQL, data visualization tools, and statistical computing [3].

If you're considering earning a degree to break into the field, you'll spend around four to five years earning a bachelor's degree (in computer science or a related field) and an additional two years earning a master's degree. This timeline can vary depending on your chosen course and method of study.

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How to become a data scientist without a degree

Many employers request at least a bachelor's degree for entry-level data scientist roles. However, it's possible to pursue a data science career without a degree.

Some employers are willing to hire candidates with the proper skill set who are up-to-date with the latest technologies and methods. Focus on building your data science skill set and earning alternative credentials (sometimes called micro-credentials) to demonstrate your competency to employers. Follow the suggestions below for more guidance.

Build technical skills in data science.

The list below outlines some of the most in-demand technical skills for data scientists.

Learn at least one programming language.

A few of the most commonly used programming languages among data scientists include: 

Read more: Python or R for Data Analysis: Which Should I Learn?

Familiarize yourself with key data science technologies.

Core platforms and technologies data scientists may use day to day include:

Read more: 7 Skills Every Data Scientist Should Have

Strengthen workplace skills for data scientists.

Data scientists must competently determine the best way to process, analyze, and articulate data findings to people of various backgrounds. Here are a few of the most crucial workplace skills to sharpen for a successful career in data science:

  • Problem-solving skills

  • Verbal and written communication skills

  • Teamwork

  • Curiosity

  • Persistence

  • Agreeableness

  • Leadership

  • Articulation

Further your education in data science.

Certifications and certificates are an excellent way to fill the gaps in your knowledge and enhance your resume, whether you've earned a degree or not. Top certifications for data scientists in 2024 include:

Read more: Your Guide to Data Science Certifications in 2024

I liked that the program had introductory courses covering a wide range of topics with practical assignments, engaging and clear video lectures, and easy-to-understand explanations. As with the other courses I took on Coursera, this program strengthened my portfolio and helped me in my career.

— Mo R., on taking the IBM Data Science Professional Certificate

How to become a data scientist with no experience

This next section walks through the steps to become a data scientist without experience. Keep in mind that everyone's journey is different. The step-by-step below follows the career path of someone wanting to earn a degree, build a portfolio, apply for an entry-level role, and work up to the data scientist title.

1. Obtain the necessary education. 

Fifty-one percent of data scientists have a bachelor's degree, 34 percent have a master's degree, and 13 percent have a doctorate. Typically, data scientists major in computer science, statistics, or mathematics. Relevant but rarer majors for this role include physics, electrical engineering, economics, and computer engineering [3].  

Read more: Data Science Major: What You Need to Know Before Declaring

2. Sharpen your skills and enhance your resume. 

The skills you should focus on may vary depending on the industry you'd like to work in. Consider browsing job postings for positions you'd like to apply to. You can gain insights about industry-standard tools and technologies and in-demand programming languages. Then, you might supplement your education by earning a certificate in a particular programming language, taking online classes, or becoming certified in a specific platform.

Another way to stand out from other candidates is to build a strong portfolio. Your portfolio can include academic projects, freelance work, and even personal projects as long as they adequately demonstrate your skills and represent your own work. If you're looking for ways to bulk up your portfolio, consider checking out the list of Guided Projects below. You'll accomplish job-relevant tasks with expert-level guidance every step of the way. 

3. Apply for an entry-level data scientist job. 

Now that you've gained the necessary skills and experience, you can start applying. Data scientist jobs requiring little or no experience will often be listed as Data Scientist (Entry-level) or Junior Data Scientist. Here are a few other entry-level data science titles to keep an eye out for during your job search:

You might also consider preparing with an industry leader by enrolling in IBM's Data Scientist Career Guide and Interview Preparation course. 

Data scientist job search resources

Further your data science knowledge with Coursera 

IBM's Data Science Professional Certificate strongly emphasizes applied learning. Once you've earned your certificate, you can add popular tools like Jupyter, GitHub, R Studio, and Watson Studio to your resume. 

Or learn how to leverage generative AI, specifically Microsoft Copilot, in your data science workflows with the Microsoft Copilot for Data Science Specialization. You'll use Copilot to analyze data, generate insights, streamline data preparation, create visualizations, and effectively communicate findings.

Article sources

1. 

US Bureau of Labor Statistics. "Occupational Outlook Handbook: Data Scientists, https://www.bls.gov/ooh/math/data-scientists.htm." Accessed September 12, 2024.  

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