Advances in technology have filled our world with information. This digital economy can present challenges, but also opportunities to improve strategic thinking in health care and several other industries. The data science profession plays an essential role by finding insights from big data that help businesses make strategic decisions and optimize outcomes.

Data scientists uses computer science and mathematical and statistical concepts to analyze massive amounts of information. Professionals are also experienced with several programming languages like Python, R, SQL and SAS. The field has exciting applications for several academic areas and nearly every sector of industry.

What does a data scientist do?

Drawing insights from massive data is a complex process that involves the following:

  • Carefully ask probing questions to identify a business problem and an approach to solving it.
  • Responsible data stewardship: A successful data scientist must be able to implement best practices for data management and stewardship, as well as conduct research in an ethical manner that maintains data security and privacy.
  • Acquire data from sources such as databases, online repositories and webservers.
  • Clean up data by addressing missing values, inconsistent data types, and other issues before it is mapped for transmission. This skill—data wrangling—is key to be an effective data scientist.
  • Perform exploratory analysis to determine variables for model development.
  • Select the data model for your analysis.
  • Apply methodologies such as machine learning, artificial intelligence and deep learning.
  • Communicate your findings with data visualization so that less technical partners will understand the business implications of your work.

data science graphic

Learn the skills and methods you need to enjoy a rewarding career in data science with Meharry.

Data science career trends

The need to draw important insights from massive data has made data science an in-demand technology profession. In fact, Glassdoor listed data scientist third on its list of 50 Best Jobs in America for 2020. Future projections remain bright as the number of jobs should increase by 28% by 2026.

Additionally, data science has expanded its influence outside of tech to nearly every industry. Today, some of the top industries with demand for data science include health care, telecommunications, e-commerce and grocer companies, finance, and cybersecurity.

Compensation is another positive sign for prospective data scientists. The average data scientist salary of $114,012 follows in line with the demand for professionals.  That pay should increase in the future, especially for those with more experience and expertise.

Data scientist career outlook

What data science position is right for you?

The data science profession is comprised of so many roles that it can be difficult to keep track. You will also find that salaries vary according to role and job title—in addition to factors like experience, industry, location, etc. The preferred skills are also different for each position, which also allows you to explore areas of data science according to your strengths and interests.

Data Science roles

The following list, pulled from altexsoft.com, will help you consider where you may find your place in the data science field.

Chief Analytics Officer/Chief Data Officer: A key leadership role. Preferred skills include data science and analytics, programming skills, domain expertise, leadership and vision.

Data analyst: Responsible for proper data collection and interpretation activities. Preferred skills include R, Python, JavaScript, C/C++ and SQL.

Business analyst: This role helps convert business expectations into data analysis. Preferred skills include data visualization, business intelligence and SQL.

Data scientist: Solves business tasks using machine learning and data mining techniques. Preferred skills include R, SAS, Python, Matlab, SQL, noSQL, Hive, Pig, Hadoop and Spark. Biomedical data scientists should have a general working knowledge of the principles of biology, bioinformatics, and basic clinical science.

Machine learning engineer: This role combines software engineering and modeling skills by determining which model to use and what data should be used for each model. Preferred skills include R, Python, Scala, Julia and Java.

Data journalists: Improves data understanding by adding context and helps with articulating business problems and shaping analytics results into compelling stories. Preferred skills include SQL, Python, R, Scala, Carto, D3, QGIS and Tableau.

Data architect: This role works with big data and warehouses data, defines database architecture, centralizes data, and ensures integrity across different sources. Preferred skills include SQL, noSQL, XML, Hive, Pig, Hadoop and Spark.

Data engineer: Implements, tests and maintains infrastructural components that data architects design. The data engineer and architect roles may be combined. Preferred skills are SQL, noSQL, Hive, Pig, Matlab, SAS, Python, Java, Ruby, C++ and Perl.

Data Science and Health Care

The health care field has tremendous applications for data science. The explosive growth of medical information, for instance, has greatly advanced precision medicine, drug discovery and improving patient care. During the coronavirus pandemic, experts have made great use of data to track the spread of COVID-19. The benefits of data-informed decisions is clear and it seems likely that health care providers will transition to more data-driven organizations. Therefore, data scientists who choose to apply their expertise in health care could find several ways to make a positive impact on society.

Meharry’s faculty in the School of Applied Computational Sciences are great examples. For instance, Dr. Aize Cao uses predicative and machine learning methods to address clinical decision support for underserved populations. Dr. Vibhuti Gupta explores mHealth wearable sensor data analytics for early detection of post-transplant complications and toxicities associated with CAR-T cell therapy.

Located in Nashville—the Silicon Valley of the health care industry—Meharry’s M.S. Biomedical Science degree presents a great opportunity for future health care data scientists.

Next steps

Learn more

The School of Applied Computational Sciences offers two master’s degrees—M.S. Data Science and M.S. Biomedical Data Science.

Explore these programs and see how they can launch your career.


Read about the skills and methodologies you will learn through our M.S. Data Science and M.S. Biomedical Data Science courses.

Contact us

Do you have questions about our programs? Contact an enrollment advisor at sacsenrollment@mmc.edu.