Master of Science in Biostatistics and Data Science

Join an Emerging Field with Strong Career Opportunities

The world of big data in healthcare is expanding quickly, and organizations need professionals who can translate data into decisions. Graduates in this field pursue careers across:

• Academic medicine and research

• Healthcare systems and population health

• Government and public agencies

• Industry and biotech

• Clinical trials and health analytics

A master’s degree in this area can open doors to in-demand roles and strong long-term career growth.

About the Program

The Master of Science (MS) in Biostatistics and Data Science is a two-year degree that prepares graduates to extract, analyze and translate vast amounts of health-related data into actionable evidence – and communicate findings clearly to collaborators across disciplines.

The curriculum blends essential competencies in statistics, computer science and epidemiology, building the toolkit needed to work with increasingly complex biomedical, clinical and population health data.

What You’ll Learn

Graduates build competence in:

• Fundamental statistical theory

• Core biostatistics methods, including regression, survival analysis and longitudinal analysis

• Statistical and computing languages used across the field: R, SAS, Stata, Python and SQL

• Data science tools and approaches, including machine learning, data visualization, databases and data management

The program’s primary objective is to graduate professionals with strength in statistical theory, practical data analysis, big data management and high-impact communication – skills essential to supporting basic science, clinical and population health studies.

Gain Real-World Experience

Learning doesn’t stop with coursework. Students strengthen technical and collaborative skills through:

• Supervised consulting sessions

• A hands-on internship

These experiences help students apply what they learn in real research and professional settings – building confidence and career readiness.

Work with High-Quality Data and Reputable Research Teams

Students will have opportunities to work with data and investigators connected to two NIH-supported epidemiologic studies:

• Jackson Heart Study (JHS) – a major single-site study of cardiovascular disease and its causes in African Americans

• Atherosclerosis Risk in Communities (ARIC) – a study of the causes of atherosclerosis and its clinical outcomes, including variation in cardiovascular risk by race, gender and location

What Graduates Will Be Able to Do

Graduates of the program will be prepared to:

• Efficiently collect, clean, organize and analyze biomedical, clinical and population health data

• Use R, SAS, Stata and Python to reproducibly explore data, visualize results, fit models, conduct inference and translate findings

• Conduct major components of big data analysis, including extracting, storing, manipulating and analyzing large genetic and bioinformatics datasets

• Convert information from databases and data warehouses into actionable findings using machine learning and other data science techniques

• Adhere to rigorous ethical and methodological standards when analyzing real-world data

• Collaborate effectively and communicate results to support better healthcare decisions and disease prevention