Choosing the Best Degree for a Data Science Career

Data science is an exciting, critical position for companies across industries. In fact, jobs in this field are expected to grow by an impressive 25% by 2032, according to Lightcast™.

The data scientist role is one of opportunity and exploration. It’s a position where you’ll dig deep into the details in order to drive big ideas across the business. This is an ideal role for those who like to be challenged, who are curious and who are driven to help transform business operations.

Have you been considering data science as a career but aren’t exactly sure how to get started? In this article, we will look at some potential data science degree paths you could take. But first, let’s understand what data scientists do and what skills they need to be successful. 

What Do Data Scientists Do? 

Data scientists sit at the confluence of technology, science and math. These experts use their skills in those three areas to manage data sets, find trends within data packages and use those trends to develop directional solutions that will drive the business forward.

So what does that look like?

A data scientist starts their day obtaining the latest data. They’ll spend some time researching that data to have a better understanding of the information it contains and the context of where and how that data was collected.

They will have some predetermined business-driven assumptions that drive their approach. The data scientist will analyze the data on hand to understand what information it presents and if those initial assumptions were correct. This may involve writing and running an algorithm, using distance calculations or running statistical models.

Once they have thoroughly reviewed everything, and from every angle, they will spend time considering how the information discovered can be used to solve current or future business needs.

Where is Data Science Needed?

Data science is not just a need in big business or tech companies. More and more industries are seeing the benefit to having a data scientist as a key team member. 

Formula 1 racing teams have turned to using data scientists to help them review tire life, fuel ranges, motor and tire temperatures, and other data points. In this sport where the difference between first and last can be seconds, using data to make informed decisions around what move to make and when can be the key to victory.

Data scientists are also key members of the engineering team at Tesla. The electronic vehicle manufacturer has data scientists onboard to review performance numbers and use data-modeling to help design next gen manufacturing processes.

Netflix, along with every other streaming service, uses vast amounts of data to determine what shows to suggest. Finding the “suggestions” in all of that data are data scientists. Martin Tingley, on the Netflix TechBlog explains “Data scientists apply the scientific method to improve the Netflix experience for current and future members, and are involved in the whole life cycle of experimentation.” 

What Qualifications Do I Need to Be a Data Scientist? 

The most successful data scientists are ones who are able to perfectly fuse computer skills, statistical understanding and mathematics in a way that enables them to find business solutions in multiple data sets. If we broke down these skills further we’d find a needed proficiency in:

• Data Skills: The data scientist must understand what data to extract, from where and how in order to drive their analyses. This typically includes training in the big data platforms, data warehousing and database management. 
• Technical Proficiency. A data scientist should have technical proficiency in computing abilities to apply machine learning to large datasets for analyses and predictions. This typically includes learning languages like R, Python or SQL.This also includes mastering data visualization tools such as Tableau or Microsoft BI. 
• Mathematical Skills. It’s important to be able to work with the data that has been captured which means an understanding of mathematics, statistical modeling, calculus and risk analysis.
• Education & Certifications. Companies have put a premium on the importance of data which is why they aren’t just looking for someone with skills but with the education and experience to know how to put those skills to use in the most effective way possible. This means job seekers should have a relevant bachelor's degree at a minimum. Certifications and industry certifications show a dedication to stay ahead in the field.

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An additional “bonus” can be your experience with tools like Github, Azure, Cloudera and MATLAB.

Which Degrees are Best for Data Science?

If you’re considering earning a bachelor’s degree to prepare you for the field of data science, you have several options. Students routinely major in mathematics or computer science. Here’s a look at the most ideal bachelor degree paths for this field. 

Top Bachelor Degrees for Data-Science

• B.S. in Computer Science: This degree is a natural fit for a career in data science with its emphasis on programming languages. Earning this degree gives you a strong technical foundation and familiarity with today’s industry-standard tools.
• B.S. in Statistics: This degree is a strong choice for prospective data scientists because statistical analysis skills are the foundation of turning large data sets into meaningful insights. With this degree, you’ll have the knowledge to understand the science of analytical decision making and build timeless skills that will always be essential in this field.
• B.S. in Applied Math: This degree is a good fit for data professionals because it focuses on applying analytical and computational math techniques to solve real-world problems. This is an ideal degree if you want to build versatile and critical problem-solving skills.

Top Master’s Degrees for Data Science

If you are looking to advance your career in the field of data science, you may want to consider pursuing a master’s degree which can help you gain a deeper functional expertise while also getting exposure to leadership principles. 

• The M.S. in Data Analytics is the best fit for professionals who want to connect data with how it can lead to creating a competitive business advantage. Curriculum in Big Data analytics and mining, data visualization and reporting, advanced analytics and statistical concepts can give professionals the tools to reach senior-level positions.
• An M.S. in Computer Science is beneficial for professionals who want a greater focus on engineering and programming skills. Relevant curriculum in this program includes advanced data structures and programming, issues in database management, applied machine learning and application of artificial intelligence.

Which Certifications are Best for Data Science? 

Professional certificates and certifications are valuable tools for career advancement. There are a wide variety of credentials offered in the data analytics field—from professional organizations to individual software providers. 

The most popular certifications include: 

IBM Data Science Professional Certificate 

What You’ll Gain: You’ll learn Data Science methodologies like Data Visualization, Data Analysis using Python, data collection in SQL databases and machine learning modeling using SciPy and Scikit-learn.

Who It’s For: For data-science professionals who rely on IBM’s technology stack to develop their analyses. 

Associate Certified Analytics Professional (aCAP) 

What You’ll Gain: Certified Analytics Professionals provides one of the leading industry certification programs by providing a high-level focus on the “7 Domains of the Analytics Process.” The aCAP certification provides recent college graduates who have minimal practical experience with an opportunity. 

Who It’s For: The aCAP is for recent graduates or entry level practitioners who lack the practice experience that is essential to earn more advanced certifications. 

Franklin University Graduate Certificate in Data Analytics 

What You’ll Gain: Franklin University offers a certificate program that will boost your knowledge of statistics, databases, data visualization, data mining and Big Data technologies using high-demand tools such as R and Tableau. You’ll learn this from seasoned, in-field practitioners who will be able to help you take lessons out of the classroom and into the practical world of business.

Who It’s For: Data professionals who are looking to accelerate their professional development, qualify for leadership roles, or increase their earning potential with an organization. 

Picking Your Path

There are many ways to begin, or continue, your career in data science. What’s important is that you consider all of the information and make an informed decision on where you want your career to go. Or in other words, practice a little data analysis to plan your career growth.

“The demand [for data analysts] in the job market has grown and will likely continue to grow in the next decade since the sheer amount of data that is created, copied, captured, used or consumed has been increasing tremendously,” said Nimet Alpay, chair of the M.S. Data Analytics program at Franklin University.

The answer for your next step may be Franklin’s M.S. in Data Analytics program, which enables you to take advantage of the rising demand for analytics skills and effectively prepares you for the analytics-related jobs of today and tomorrow. 

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