Master of Science – Health Data Science

About

The SM in Health Data Science is designed for students who want to build advanced quantitative and computing skills and apply them to consequential questions in health and medicine. 

As a student, you will: 

• Develop expertise in statistical inference, statistical computing, machine learning, production data science, AI systems, epidemiology, and statistical collaboration;  

• Learn to manage and analyze large-scale health data to identify patterns, trends, and associations;  

• Build skills in evaluating models, interpreting results, and communicating findings;  

• Shape your training through a broad selection of elective courses;  

• Learn within a community of scientists and educators working to improve health through advanced quantitative research; and  

• Prepare for a career in health data science or further doctoral study in data science, biostatistics or related quantitative and computational fields. 

On Campus (Fall start) • Full-time (2 years; 4 semesters)

Curriculum

Competencies

This 80-credit program is designed to provide students with targeted skills and knowledge required for work in health data science. These specific skills and knowledge domains are:

1. Recognize study design and its scientific and/or societal context.
2. Practice data gathering, preparation, transformation, and exploration.
3. Prepare data visualization, presentation, and communication.
4. Employ appropriate computing paradigms for efficiency and reproducibility.
5. Evaluate modeling context, apply suitable models and methods, and interpret results.
6. Design, deploy, and maintain production-ready machine learning and AI systems for health applications, including multi-agent architectures, applying MLOps principles to ensure reliability, scalability, monitoring, governance, and equitable real-world impact.

The SM in Health Data Science is intended as a terminal professional degree that will enable students to launch their careers in health-related data science. However, it can also provide the foundation for further doctoral studies in data science, biostatistics, or other quantitative or computational sciences. 

Students will receive training in quantitative methods, including applied regression, statistical inference, statistical computing, machine learning, production data science, AI systems, epidemiology, and statistical collaboration. 

Our Community

Health Data Science students learn in a community of scientists, educators, and peers from around the world, with access to resources that support technical development, research, career exploration, and the transition to graduate study.

Program and School resources include:

• Opportunities to conduct research with faculty and staff across Harvard Chan, Harvard University, and MIT;
• Career services and networking opportunities;
• Resources for strengthening coding and statistics skills;
• Research support through the Countway Library of Medicine;
• Academic coaching and tutoring; and
• More than 40 student organizations focused on public health issues, cultural affinities, and extracurricular interests.

Beyond the classroom, student organizations and offices across Harvard Chan offer opportunities to connect with the School community and participate in events on campus and throughout Boston.

Career Outcomes

The SM in Health Data Science prepares graduates to apply advanced quantitative and computing skills across a range of health-focused organizations and research environments. 

Potential career settings include: 

• Biotechnology and pharmaceutical organizations;  

• Health care organizations;  

• National and international government agencies;  

• Nonprofit organizations and NGOs;  

• Public- and private-sector organizations;  

• Research institutions; and  

• Universities and academic research settings.  

The program can also provide a foundation for further doctoral study in data science, biostatistics, and related quantitative or computational fields. 

Eligibility Criteria

The Master of Science 80-credit program (SM-80) requires:

• An undergraduate degree in the mathematical sciences or allied fields (statistics, economics, etc.) or computer science, with a strong interest in health science,
• Practical knowledge of computer scripting and programming, as well as experience with a statistical computing language such as R or Python,
• Calculus through multivariable integration,
• One semester of linear algebra or matrix methods, and
• Excellent written and spoken English.

Additional research or work experience would be considered beneficial, but not required.

Application Requirements

All applications must be submitted through SOPHAS – the centralized application service for public health programs. In addition to the application, applicants must submit:

• Statement of purpose and objectives
• Official test scores
• Three letters of reference
• Resumé/curriculum vitae
• Post-secondary transcripts or mark sheets (World Education Services credential evaluation for applicants with degrees from outside of the United States.)
• English language proficiency (TOEFL/IELTS/Duolingo English Test), if applicable

Application Deadline: December 1

Applicants may apply to only one degree program for either full- or part-time status. Applications are reviewed in their entirety and decisions are released via email in late February/early March. Decisions are not released until all application components are received. 

Related Links