How to Become a Data Scientist

The demand for Data scientists continues to grow. Learn how to become a Data scientist and what education is needed to help realize your goals.

How to Become a Data Scientist - Education, Qualifications, Career Paths

Data-driven decision-making is increasing the demand for Data scientists across all employment sectors. Businesses must use their data strategically, and Data scientists are key to unlocking competitive advantage and growing market share.

Though it’s possible to become a Data scientist right out of college, according to a 2021 survey, as many as 87 percent of data science and analytics professionals have at least a master's degree. In fact, approximately 39% of data science openings require applicants to have at least a Master of Data Science degree. If you’re considering how to become a Data scientist to advance or transition your career, a master’s or PhD degree is not just a good investment—it’s essential to your success. Here’s what you need to do to make sure the discipline is right for you and pave your path into this influential and lucrative profession.

Data scientists usually fall into two camps – those who know math really well but don’t code efficiently, and those who are great coders but don’t have a solid foundation in statistics," said David Sullivan, Rice Alumni and Data Scientist at New Knowledge. "I can speak to both sides, so I am right in the middle – exactly where I wanted to be.

What is a Data Scientist?

Data science often gets confused with computer science. While the disciplines overlap, they're distinct fields with different applications. Data scientists are responsible for taking the raw “big data” made possible by advanced computing, cleaning it, structuring it, analyzing it, and transforming it into intuitive visual insights and recommendations. A Data scientist’s data-driven observations and recommendations help business owners and executives make effective decisions that impact growth, influence offerings, drive operational efficiencies, and improve overall performance. Data scientists are creative thinkers and collaborators who understand the valuable intersections between data, business, government, medicine and society.

Data scientists must be proficient in math and statistics, with strong communication and collaboration skills. They also need basic-to-intermediate programming skills (particularly Python and R) that allow them to develop machine learning based algorithms and query databases, among other responsibilities.

Data Scientist vs. Computer Scientist

While both occupations operate on the cutting-edge of digital innovation, Data scientists and Computer scientists apply their skills differently. Computer scientists are versatile “generalists” with the depth and breadth of computational knowledge to ideate, develop and build a range of digital tech innovations.

Data scientists, on the other hand, love the answers enabled by computer scientists’ advanced, secure systems. Data scientists and computer scientists partner across functions--from strategy to product, marketing to operations--to iteratively evolve and improve.

Data Scientist vs. Data Analyst

Within their occupation, Data professionals can also specialize in a particular area of focus or interest.

Data analysts focus on different types of databases, applications and privacy regulation, using SQL skills to query those databases, and then Tableau or Power BI to visualize and communicate sensitive data and insights to mid-level management.

The ubiquity of big data across all industries and disciplines now requires Data scientists who are well versed in all of previously mentioned fields. Data scientists are increasingly synonymous with big data, machine-learning based algorithms and Python or R programming, mining and synthesizing big data to solve some of business’s and society’s biggest problems.

Becoming a Data Scientist: Education Requirements, Qualifications & More

Becoming a Data scientist requires an advanced understanding of machine learning algorithms, statistics, mathematics, programming, and data visualization. Though it’s possible to start working in the field with minimal training or experience, a Master of Data Science or advanced degree is often preferred, if not required, as professionals strive for promotion into mid-level or executive Data science roles.

What Education is Needed to Become a Data Scientist?

As with any technical field, data science requires a strong educational background to ensure that graduates are prepared for professional demands. A bachelor’s degree in computer science, data science, engineering, or machine learning will set you up for success, but it’s not the only way to get the background needed to fulfill a data science education requirement.

Data Science Bootcamps vs. Master’s Programs

Bootcamps, specifically those that focus on building strong coding and programming skills, will help those with degrees outside of computer and data science prepare to transition into the field. The Rice University Data Analytics & Visualization Boot Camp can help students upskill or reskill for data analysis, analytics and visualization roles.

Data Science, however, is a discipline that rewards mastery. More than 39% of employers looking to fill data science roles prefer applicants with at least a master’s degree. That graduate-level experience ensures you have an understanding of the computational and statistical foundations of data science—the backbone upon which you’ll build your career.

Individuals who are certain they want to pursue the data science path might consider an online Master of Data Science, which will allow the flexibility to continue working while earning a master's part-time. Programs like Rice's online Master's in Data Science allow you to specialize in either Machine Learning or Business Analytics.

When is the Right Time to Pursue a Data Science Master’s Degree?

If you are seeking a career switch or career advancement, or if you are an undergraduate student who wants to improve your career prospects.

Many students work for at least 1-2 years prior to pursuing their master's degree, although this is not a requirement. This experience affords them a greater level of certainty in terms of career aspirations and skills they need to develop. At Rice, our online graduate students have anywhere from 1 to 20+ years in the workforce, so the best time to pursue a data science master's degree is when it makes sense for you, both professionally and personally.

An online master's in data science (like Rice Online MDS) provides convenience and flexibility, allowing professionals to pursue their graduate experience while continuing to work part-time, from anywhere.

What Qualifications Are Required to Become a Data Scientist?

As a professional Data scientist, you’ll need a graduate-level understanding of the following subjects:

Foundational Computation & Math Skills

One prerequisite for a data science career is an understanding of the foundations of computer science and data analysis. You’ll need to understand advanced mathematics, statistics, computer programming, and statistical analysis.

Many of these skills can be learned through a bachelor’s degree in mathematics, computer science, or statistics. However, many non-Computer Science, non-STEM students and career changers with non-technical degrees are able to acquire these skills through bootcamps and/or self-study. For example, Rice offers dozens of highly-rated, free online non-credit courses ranging from Python Programming Essentials to Algorithmic Thinking, and more.

Foundational Knowledge of Programming Languages for Data Science

Programming may not be a daily responsibility for all Data scientists, but just over 70% of Data scientist job postings ask for Python programming skills, among other programming languages. Data scientists should have basic-to-serviceable programming skills to help mine and manipulate big data.

Practical, Real-World Data Science Skills

Many employers look for applicants that have demonstrated real-world experience solving data science problems. The best way to prepare yourself for a career in data science is to seek out projects that will help sharpen your skillset and build a portfolio with real-world big data sets.

These projects will give you experience working with different types of data ranging from structured and unstructured data sets to geospatial data, video and images at scale. The more types of data you work with before entering the field, the better prepared you’ll be to take on different, more challenging tasks in the workforce.

In the Master of Data Science program at Rice, our students gain valuable project experience via the Capstone course. They put theory and knowledge into practice on real-world data science applications from business, government and non-profit sectors, all with the individualized support and backing of expert Rice faculty.

Data Visualization Skills

Part of every Data scientist’s job is to create intuitive visual presentations of the data they are managing and analyzing. This allows subject matter experts (from physicians and doctors, to business executives) to better understand the underlying data and strategic recommendations.

You’ll need a firm understanding of common data visualization tools like Tableau, PowerBI, Infogram, and Plotly. You can learn to use these programs on your own, but you’ll also gain hands-on experience with these platforms during the coursework for your Master of Data Science degree.

How Long Does It Take to Become a Data Scientist?

The amount of time it will take for you to become a Data scientist largely depends on the level of education and degree program you choose, the speed at which you complete the program (full-time or part-time), and how many years of work experience you have. If you have a background in computer science and already have math and/or programming foundations, completing additional coursework and entering the workforce can happen more quickly.

However, if you’re working full-time while pursuing an online Master of Data Science degree, it may take two to three years to complete your master’s program part-time.

Making a Career Change to Data Science

The prospect of changing careers can be daunting, but moving into the Data Science and Analytics occupation is a great decision because of high salaries and growing demand across industries.

At Rice, many of our students join the Online Master of Data Science exactly for this reason: to switch careers into Data Science, Big Data Analytics or Business Analytics. How to make the career change depends on your background and current strengths:

  • If you have a background in math or are already proficient in linear algebra, calculus and/or statistics: Start with a free, beginner-level Intro to Python programming course to build your computational/computer science foundations. Data Scientist use machine learning algorithms to analyze big data at scale, so the computer science side is important.
  • If you have a background in computer science or engineering: Start by refreshing yourself on the math fundamentals like linear algebra, calculus and statistics. This math is critical when it comes to creating the machine learning models and frameworks you'll use for complex data analysis. If you have coding experience already, Python should be fairly easy to pick-up.

Rice University offers free online Coursera courses that can help you explore opportunities to make a potential career change into data science.

Data Science Career Paths & Job Outlook

Demand for Data scientists is increasing by the year as more organizations recognize the power of big data to achieve competitive advantage. With the necessary education, prerequisites and/or experience, you’ll be able to enter the field and pursue different career options as a Data scientist. These include:

  • Data Scientists
  • Machine Learning Engineers
  • Big Data Analysts
  • Research Scientists
  • Statisticians
  • Data Strategy Managers
  • Business Intelligence (BI) Developers
  • Chief Data Officers

These are just a few of the specialized career paths available to Data scientists across most industries. You’ll be able to follow your passions and choose a position in an industry that will help you reach your long-term career goals. Learn more about the different data science career options.

Become a Data Scientist: Pursue a Data Science Master Degree at Rice University

If you’re interested in becoming a Data scientist, whether you’re just beginning your career or looking to make a career change, investing in your education and portfolio is a great best place to start. Learn more about the online MDS@Rice program today. When you enroll, you’ll be able to take advantage of a curriculum that matches what employers want, work with the top experts in the fields of Machine Learning/AI and top-ranked Business Analytics, and surround yourself with smart, driven peers who will push you to do your best work each day.

Data Science employment is projected to grow +35% between 2022-2032.

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