MS - HDS Concentration

The MS in Biostatistics with area of concentration in Health Data Science is designed for students with a background in calculus, some experience with a programming language, and a strong interest in public health and data science. The HDS concentration emphasizes biostatistical theory and statistical computational methods for analyzing, processing and interpreting large-scale data sets so that students are prepared to clean, store, manage, manipulate, visualize and process high dimensional data as well as be effective statistical collaborators in interdisciplinary studies; and lead the design and execution of studies.

Biostatistics and HDS Careers

Addressing the rising need for health care analytics, our HDS concentration provides cross-disciplinary and necessary training for graduates of our program to be in high demand. In fact, Glassdoor ranks data scientist as the #1 best job in America for 2019 and Forbes magazine states “IBM Predicts Demand For Data Scientists Will Soar 28% by 2020. Here are just a few employers with open positions for health data scientists found on a recent search on Indeed, Glassdoor and ZipRecruiter:

  • Amazon
  • Fortive
  • GNC
  • Google
  • Highmark Health
  • Innovu
  • RAND
  • Thermo Fisher Scientific

Typical median salary ranges were $56,000-$125,000.

HDS Concentration-specific Competencies

Students with the health data science concentration will master the core MS in biostatistics competencies and will also be able to:

  1. Apply data curation and data management techniques such as data munging, data scraping, sampling, and cleaning in order to construct informative, usable, and manageable data sets for meaningful analyses,
  2. Apply methods for big data and machine learning to reveal patterns, trends and associations including visualization, and
  3. Effectively use a programming language (such as R and/or Python) for data management and statistical analysis.

HDS concentration-specific Requirements

40 credits, including:

  • Coursework in fundamentals of statistical theory and applications,
  • Coursework in programming languages (e.g. SQL, R, SAS, Python),
  • Coursework in data science, machine learning and database management,
  • A statistical consulting practicum,
  • Coursework in epidemiology and public health, and
  • Capstone course to prepare a thesis involving innovative data analysis or related to an internship experience.

Program Information

MS-HDS Schedule (PDF, 2022-23)
MS-HDS Degree Requirements Worksheet (PDF, 2022-23)
Student Handbook (PDF, 2022-23)


Sample Thesis Titles

Browse titles in D-Scholarship, the institutional repository for research output at the University of Pittsburgh

"The proliferation of master’s and doctoral programs in data science and analytics continues, seemingly due to the insatiable demand of employers for data scientists." - Amstat News, 2019