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 earn higher-than-average salaries and generally feel satisfied with their work-life balance [2]. If you're considering starting or switching to a data science career, read on to learn more about the role and its requirements. 

How long does it take to become a data scientist?

The amount of time it takes you to become a data scientist depends on your previous experience, education, and skills. Suppose you're transitioning into data science from a related career such as software engineering or machine learning. In that case, gaining the required competencies through certificate programs or online classes may only take a few months. If you're considering earning a degree to break into the field, you'll spend four years earning a bachelor's degree, an additional two years earning a master's degree, and between three and six years for a PhD. This timeline can vary depending on your chosen course and method of study.

Linked image with text "See how your Coursera Learning can turn into master's degree credit at Illinois Tech"

How to become a data scientist without a degree

Many employers request at least a bachelor's degree for entry-level data scientist roles. If earning a degree is outside your plans, you have other options. Data science is an in-demand and rapidly evolving field. 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. 

Read more: New Coursera survey shows high demand for industry micro-credentials from students and employers in tight labor market

Technical skills for aspiring data scientists

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

Programming languages

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?

Technologies

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

Read more: 7 Skills Every Data Scientist Should Have

Workplace skills for data scientists

Data scientists possess a combination of technical and workplace skills. This role involves working with various software programs, programming languages, people, and data types. 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

Certificate programs and online classes for aspiring data scientists

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

Tip for entry-level professionals

As a beginner data scientist, it's helpful to learn from others. Follow reputable data scientists on social media, YouTube, or other outlets to learn from their experiences and improve your present ones.

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Take the next step toward becoming a data scientist 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. 

If you're ready to earn your bachelor's degree, consider flexible online programs like the University of London's Bachelor of Science in Computer Science. Or, supplement your bachelor's degree with a Master of Computer and Information Technology from the University of Pennsylvania. 

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Article sources

1. 

US Bureau of Labor Statistics. "Occupational Outlook Handbook: Data Scientists, https://www.bls.gov/ooh/math/data-scientists.htm." Accessed January 19, 2024. 

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