How Long Does It Take To Become a Data Scientist?

Data science is a high-demand field that focuses on data mining and storage. Typically, to work as a data scientist, you need at least a bachelor's degree.

The time it takes to become a data scientist depends on a few factors. Keep reading to learn how long it takes to become a data scientist and the factors that affect the duration of the program.

What Is Data Science?

Data science is a field of study concerned with all things data: collecting, analyzing, storing, and extracting actionable insights from data. Data scientists can work in various industries, including business, finance, healthcare, and more.

Data scientists don't just work with data but also build and maintain the systems and frameworks that help them run these processes. As a result, data science is an interdisciplinary field that combines knowledge of business, computer science, and statistics.

Learn more: What Is a Data Scientist?

Data Science Degree Timeline

Data science is usually offered as a bachelor's degree or master's degree — and sometimes as a doctoral degree. Each degree path takes a different amount of time, depending on the school and the data science degree curriculum.

Bachelor's Degree: 4 years

Bachelor's degrees are undergraduate degrees. They usually require 120 credits and take four years of full-time study on average.

Bachelor's programs usually start with required general education courses, which are meant to provide a well-rounded foundation in the liberal arts and sciences. You'll then take your core data science courses, as well as any electives or specialization courses.

Master's Degree/PhD: 2 to 6 years

Master's degrees and Doctor of Philosophy (PhD) degrees are both graduate degrees, meaning you earn them after you finish your bachelor's degree. PhDs are usually based on research, while master's degrees may also be research-focused or can hone your data science skills.

Usually, master's degrees require somewhere between 30 and 40 credit hours. On average, these programs take two years, but they can range between one and three. Some schools offer dual bachelor's and master's degree programs, allowing you to earn both degrees within five years instead of the usual six.

PhD degrees are much longer. Students usually spend two or three years in major coursework, then spend a few years researching and writing their dissertation. The time it takes to complete this program depends primarily on the duration of your dissertation.

Many programs may require you to earn a master's before you pursue a PhD. However, some programs may offer bridge programs, which take slightly more time than a standard PhD but still less time than earning both a master's and a PhD.

Alternative Paths (Bootcamps and Certifications): 3 to 12 months

Data science bootcamps and certifications are shorter programs that do not lead to a degree. They can provide a foundation in data science, or they may focus on a specific aspect of data science (i.e., data analysis or programming languages).

While this can be a great way to learn a new skill, it's important to note that these programs are not nearly as comprehensive as degree programs. Additionally, potential employers may require a degree.

Skill Development Timeline

Data scientists need multiple skills to do their jobs well. Earning a degree in this field will help you develop and sharpen these skills, and you'll continue to develop these skills through years of experience.

In addition to the technical skills we've broken down below, there are multiple soft skills that you'll need to have in your data science skill set, including:

• communication
• critical thinking
• decision making
• problem-solving

Programming and Tools: 6 to 12 months

To process and store data, data scientists need to know multiple programming languages. These primarily include Python, R, and SQL but can also include Java and Javascript.

Additionally, there are several data analysis and visualization tools that data scientists use, including:

• Excel
• GitHub
• Hadoop
• Pandas
• Spark
• Tableau
• Tensorflow

While you might not need to know how to use each tool, you'll need to know the fundamentals of what these tools are and how they help you with your datasets.

Data Analysis and Statistics: 6 to 12 months

Data analysis and statistics are a core part of any data scientist role. Data scientists use these tools to create algorithms and develop predictive models.

Most programs require at least one course in probability and statistics, as well as courses that cover data analytics. As a result, you may be studying these topics for a year.

Machine Learning: 6 to 18 months

Artificial intelligence and machine learning are common tools within the data science field. Data scientists need to understand not only how these systems work, but how to tweak them to perform actions as needed.

Courses on machine learning cover various topics, including natural language processing, deep learning, neural networks, and machine learning algorithms. Some students choose a specialization in this field to become machine learning engineers.

Data Visualization: 3 to 6 months

Data visualization refers to taking big data and breaking it down visually, (e.g., using graphs or charts), to make the information easier to understand, especially when communicating with stakeholders. Your program should cover best practices for data visualization and the common tools used in data science projects (i.e., Tableau and Power BI).

Most degree programs include one or two courses on data visualization, which means you'll spend a few months learning the topic.

Practical Experience Timeline

Many data science programs include hands-on experiences to give students a better understanding of the field. We've broken down some common practical experience options below.

Internships and Projects: 3-12 months

An internship is a common part of a degree program. Internships allow you to earn in-person experience and mentorship from someone in the data science field. Often, they can transition into full-time jobs or allow you to network with professionals who can hire you for other roles.

Many degree programs also include projects. These may be smaller projects with specific focuses scattered throughout the program, or a capstone final project to showcase what you've learned.

Competitions and Portfolio Building: Ongoing

Even once you've launched your data science career, you have many opportunities to increase your knowledge base through hands-on learning. These include competitions, building your portfolio, and professional development.

Technology is constantly evolving, and so is the field of data science. Participating in this kind of practical experience keeps your skill set up-to-date.

Factors Influencing How Long it Takes To Become a Data Scientist

We provided a general timeline above for data science learning. However, there are a few things that can influence how long it takes to become a data scientist.

Prior Experience

If you already have college credits, you can often transfer them into your degree program. This allows you to make use of time and money you've already spent and can shorten the overall length of your program.

Some colleges and universities also offer college credit for life experiences. This is often for things like work experience or military experience.

Learning Pace

The pace at which you earn your degree plays a big role in how long it takes you. For example, a full-time schedule will allow you to earn a bachelor's in about four years, while an accelerated schedule shortens the time frame and a part-time schedule makes it longer.

To accelerate your degree, consider choosing a faster-paced program. You can also take courses during the summer to shorten the overall length of your program.

Market Opportunities

Just because you have a degree doesn't mean you'll find a data scientist job right away. While the job market for data scientists and data analysts is pretty good, how long it takes you to get a job will depend on several factors, including where you live.

Find a Data Science Program Today

If you're interested in data science, check out the featured programs on Learn.org. Reach out to individual schools to get in-depth information on the programs they offer.