Data Scientist vs. Data Analyst: Which Career Is Right for You?

Students interested in gathering, organizing, interpreting, and utilizing data have many potential career options. These opportunities are only expanding as companies and organizations increasingly rely on information gathering and data analysis to make decisions. Data scientist and data analyst are two rewarding and diverse potential career paths in this field. While they share a number of common characteristics, there are also differences between the two. Both are valuable, especially in today’s data-driven world, but they play to different strengths and offer different career trajectories.

Understanding the similarities and differences of a data analyst vs data scientist is helpful for students who are considering advanced studies in data science, allowing them to choose the program that best fits their needs.

Data analyst look at a laptop screen in a server room

Data Scientists and Data Analysts: A Career Overview

Both data scientists and data analysts focus on analyzing data. However, there are also distinct nuances between the two. A data scientist’s primary duty is to collect data, and these individuals tend to be more involved in programming machines and optimizing systems. On the other hand, a data analyst focuses more on organizing data to identify trends, curate meaningful insights, and communicate the implications of collected data.

What Does a Data Scientist Do?

Data scientists often spend their time improving the effectiveness of programs that collect and analyze data. With a strong background in computer programming, machine learning, data mining, and deep learning, those who pursue a career in data science are often responsible for the machines that store and interpret information. Effective data scientists are skilled in a variety of programming languages, as well as statistical analysis and data interpretation.

According to the U.S. Bureau of Labor Statistics (BLS), computer and information research scientists enjoy a median salary of $114,520. This career path, which includes data scientists, is in the midst of a growth trend. The BLS anticipates a 19% increase in data science jobs between 2016 and 2026.

What Does a Data Analyst Do?

Data analysts tend to spend a great deal of their work hours searching data for useful insights and trends. They then communicate what they’ve learned to company stakeholders, along with recommendations for moving forward. This allows businesses to address problems in their industry, find missed opportunities for growth, and develop data-driven business plans. The capacity to parse data and find the underlying trends requires a strong mathematical foundation, analytical skills, and the ability to confidently communicate findings and make recommendations.

The BLS predicts that companies will create over 30,000 new data analyst jobs between 2016 and 2026 — more than a 27% increase. With a median pay of $81,390 per year, data analysis represents a valuable opportunity for individuals interested in leveraging an advanced degree in the field.

Possible Paths for Aspiring Data Scientists

Those pursuing a job in either data science or data analysis will likely consider one of two advanced degrees: a Master of Science in Data Science or a Master’s in Business Data Analytics. Both degree programs offer potential paths to working with data in powerful ways. That said, each program presents its own focus and opportunities.

Master of Science in Data Science

Students interested in pursuing a career as a data scientist — with a stronger emphasis on computer programming, coding, cloud computing, and machine learning — could benefit from earning an advanced degree. Online master’s in data science programs focus on developing students’ proficiency in high-demand skills.

Through the program’s curriculum, students encounter various coding languages, such as Python, SQL, SAS, and R. Participants also select elective courses that support specific areas of interest in the data science field. In addition, the project-based nature of a data science degree allows students to learn through action. As a result, graduates gain real-world experience and confidence in their skills, allowing them to seek data scientist positions upon graduation.

Master’s in Business Data Analytics

Those who want to learn how to take complex datasets and use them to identify trends, share information, make decisions and recommendations, and predict outcomes tend to pursue a master’s degree in business data analytics. Through the fully online program offered at Maryville University, students learn how to tell the story behind the data.

This program dives into topics like data analytics, data visualization, data mining, and forecasting. Through project-based coursework, students create charts and graphs that communicate findings, use statistical analysis to create predictive models, and draw insights and inferences from data sets. This generally prepares students for a data analyst role after graduation.

Be at the Forefront of a Data-Driven Future with an Advanced Degree

Whether weighing a future as a data scientist or data analyst, it’s clear that the era of big data has arrived, and those who can effectively manage information are in demand. In a world dominated by data, an online Master’s in Business Data Analytics or Master of Science in Data Science from Maryville University can support graduates in securing a rewarding career.

Sources:

Computerworld, “IT Job Spotlight: Data Scientist”

Dataquest, “What’s the difference between a data analyst, scientist and engineer?”

Forbes, “Bridging the Data Scientist Talent Gap Starts With Defining the Current Role”

Maryville University, Master of Science in Business Data Analytics

Maryville University, Master of Science in Data Science

U.S. Bureau of Labor Statistics, Computer and Information Research Scientists

U.S. Bureau of Labor Statistics, Operations Research Analysts