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This program helps you build a solid foundation of key principles and practical experiences to ensure that you become a well-rounded professional ready to tackle real-world challenges.

If you are passionate about the intersection of data science, biotechnology, and cutting-edge research and aspire to be at the forefront of scientific discovery and contribute to advancements in healthcare and life sciences, then you should consider this four-year, full-time program on the Boston campus. The interdisciplinary curriculum blends computer science, statistics, and data analysis with biotechnology and life sciences. This unique approach equips you with the skills to bridge the gap between data-driven insights and scientific discovery. At MCPHS, you'll engage in collaborative practice, working with healthcare professionals and peers on real-world projects. Together, you'll simulate the challenges and rewards of working in a professional environment. This program also offers the opportunity for experiential learning at health or life science companies located in two of the top biotech clusters in the United States: Boston and Worcester.

Your Four-Year Journey

This program is designed to provide a well-rounded education that combines biological sciences, data science, business, and ethics, preparing graduates with a comprehensive skill set for a career in biotechnology research and development. This program is STEM-designated, qualifying international students for an additional two years of OPT work in the United States.

First-Year Experience

master calculus
establish a strong foundation in the biological sciences and medical terminology
begin to develop a foundation in biomedical informatics
build critical communication skills including in writing and verbally

Second-Year Experience

study chemistry
develop foundational knowledge in programming
develop strong quantitative skills in statistics and linear algebra
explore the intersection of biotech and business

Third-Year Experience

learn data analysis using programming languages such as R
delve into big data and machine learning
study biostatistics and public health research methods
explore legal, compliance, and ethical issues related to data and health data collection management

Fourth-Year Experience

gain practical experience in data science through professional experiences
advance knowledge in machine learning and deep learning
acquire specialization through elective courses in behavioral science, humanities, or other specific data science disciplines
master data visualization and display

Learning Outcomes:

Upon completion of the program, students will be able to:

Apply fundamental principles of data science, including statistical modeling, data management, and data manipulation, to identify patterns and gain actionable insight to address challenges in industry, life sciences, and healthcare.
Design workflows and applications as solutions to organizational challenges.
Collaborate across teams and functions to define problems, identify appropriate data, analyze sufficiency, and create visualizations to support communication and decision-making.
Communicate effectively about properties of computer coding, task workflows, databases, and issues with data, including sufficiency, representation, and distributions.
Explain machine learning, algorithms, and ethical challenges they represent in context with data science and their impacts on society.
Evaluate data integrity and sufficiency and critically question analytical methods and approaches to manipulation across large data sets.
Describe critical insight derived from large data sets.