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)
MS-HDS Degree Requirements Worksheet (PDF, 2019-20)
Student Handbook (PDF, 2019-20) 

Admissions

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

Application Deadline

Applications for fall admission are due by April 1 for international applicants and July 15 for US applicants.

Apply online now

Using  SOPHAS, the centralized application service for graduate schools of public health.

Questions?

biostat@pitt.edu

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MS Student & Alumni News

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DiSanto awarded Commonwealth Equity Scholarship 

DiSanto awarded Commonwealth Equity Scholarship

Dominic DiSanto (BIOST '20) was awarded the Commonwealth Equity Scholarship for the academic year of 2019-20.  (12/17/2019)
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Clemons awarded Commonwealth Equity Scholarship 

Clemons awarded Commonwealth Equity Scholarship

Arvon Clemons (BIOST '21) was awarded the Commonwealth Equity Scholarship for academic year 2019-20.  (12/17/2019)
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Meet Ruishen Lyu, MS student in biostatistics 

Meet Ruishen Lyu, MS student in biostatistics

Just like with his interest in preventative medicine, Ruishen Lyu (BIOST MS '20) had two main reasons for choosing Pitt from among the other universities to which he was accepted. The first was the great reputation of a large research university like the University of Pittsburgh. The second was the... (01/29/2020)
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Meet Ashika Mani, accelerated MS student in statistics and biostatistics 

Meet Ashika Mani, accelerated MS student in statistics and biostatistics

Ashika Mani (BIOST MS '21) joined Pitt Public Health this year via our Accelerated Bachelor's/Master's Program. “It was a pretty natural choice as I was looking to jumpstart my graduate studies early,” she said. “I was almost done with my undergraduate requirements.” She felt like she had so much m... (12/11/2019)
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Meet Dominic DiSanto, MS student in health data science 

Meet Dominic DiSanto, MS student in health data science

“I’m especially excited about my health data science concentration. It’s a very dynamic skill set and one that translates well to all different kinds of problems," said Dominic DiSanto (BIOST MS '21). "The curriculum in general looks like a very applied curriculum and the idea of having a consultin... (12/11/2019)
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Meet Arvon Clemons, MS student in statistical and computational genomics 

Meet Arvon Clemons, MS student in statistical and computational genomics

Part of what led Arvon Clemons to Pitt Public Health was the city of Pittsburgh. He felt a connection to a city that was similar to his hometown of St. Louis. His academic background doesn’t feel as congruous with his current study. But ultimately, both the city and the program are turning out to b... (12/09/2019)
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Meet Lingyun Lyu, Pitt Biostats MS graduate and PhD candidate  

Meet Lingyun Lyu, Pitt Biostats MS graduate and PhD candidate

Lingyun Lyu (BIOST PhD '22) is a second-year Ph.D. student in Biostatistics at Pitt Public Health. She came to Pitt in 2016 and earned her M.S. in Biostatistics in 2018. She loved the master’s program and thinks that it’s really well-designed. In addition to many essential statistical theory and ap... (12/09/2019)
More Biostats Student Stories