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In this 36-credit master’s program, you will leverage your knowledge of data science to address the most complex challenges facing healthcare and the life sciences.

The rapidly growing field of data science leverages computer science, statistics, and logical analysis to identify patterns that illuminate previously unattainable insights and inform critical decision-making. The field has become central to advances in the medical and life sciences because it allows us to expedite research into complex processes. With our strategic location in the world’s preeminent life sciences hub and our extensive range of expertise in the healthcare and life sciences realms, MCPHS can provide you with unparalleled opportunities to build a highly competitive career in a broad range of fields. Organizations focused on consumer health, technology, healthcare finance, insurance, and biotech all need data scientists. The degree may also help experienced informaticists and managers advance their careers because of their specialized skills. While a background in math and statistics is helpful, you also can prepare for this program with a course in foundational linear functions and measures of centrality. A bachelor’s degree is required for acceptance into the program.

Your 36-Credit Journey

During this full-time, three-year graduate program, you will learn to:

Apply statistical modeling, data management, and data manipulation to support actionable insights.
Design advanced workflows and applications to solve complex challenges in healthcare and the life sciences.
Lead teams across business functions to define problems, identify appropriate data, analyze sufficiency, and create visualizations to drive decision-making.
Communicate effectively with multiple constituencies about properties of computer coding, task workflows, databases, and issues with data, including sufficiency, representation, and distribution.
Explain machine learning, algorithms, and the ethical challenges they represent in context with data science and their impacts on society.
Evaluate data integrity and sufficiency and make recommendations to resolve issues.

You may also participate in an optional fieldwork course to expand your experience in data science.

Learning Outcomes:

Upon completing the MS in Data Science, students will be able to:

Apply statistical modeling, data management, and data manipulation to support actionable insight.
Design advanced workflows and applications to solve complex challenges in life sciences and healthcare.
Lead teams across business functions to define problems, identify appropriate data, analyze sufficiency, and create visualizations to drive decision-making.
Communicate effectively with multiple constituencies about properties of computer coding, task workflows, databases, and issues with data, including sufficiency, representation, and distribution.
Explain machine learning, algorithms, and ethical challenges they represent in context with data science and their impacts on society.
Critically evaluate data integrity and sufficiency and make recommendations to resolve issues.