Online MS in Health Data Analytics
Bouvé College of Health Sciences
Master healthcare analytics, health informatics, and data science—and build the skills to drive real-world decisions in one of the fastest-growing fields in the industry.
100%
online
18+
Months
32
Credits
$24k
$750 per credit hour
Learn to turn healthcare data into real-world impact.
From electronic health records to genomics, claims data to population health tracking, the healthcare industry generates more information than ever before. The challenge isn't collecting it—it's turning it into decisions that improve lives. Professionals who can work at the intersection of health informatics, healthcare analytics, and data science are among the most sought-after in the field.
That’s where you come in. Data Scientists are projected to grow 33.5% from 2024 to 2034—making it the fourth fastest-growing occupation in the U.S. economy—with a median annual salary of $112,590.* Demand for professionals who can bridge clinical knowledge and analytics expertise is accelerating rapidly.
The Online MS in Health Data Analytics from Northeastern's Bouvé College of Health Sciences prepares you to lead at that intersection—whatever your background, and wherever you want to go.
*U.S. Bureau of Labor Statistics, Occupational Outlook Handbook, “Data Scientists,” 2024–34 projections. https://www.bls.gov/ooh/math/data-scientists.htm
Built for the intersection of healthcare analytics, data science, and health informatics.
The MS in Health Data Analytics combines a rigorous analytics core with deep healthcare-specific knowledge—preparing you not just to analyze data, but to understand the systems, stakeholders, and regulations that shape how that data is used. Whether your background is in health informatics, clinical care, data science, or business, this program meets you where you are.
Designed for working professionals, the fully online, asynchronous program fits around your schedule—not the other way around.
Program Highlights:
- Strong Analytics Core – Master data acquisition, mining, statistics, and visualization. Gain hands-on experience with R, SAS, and Python—tools used by industry professionals every day.
- Healthcare-Specific Focus – Go beyond general analytics. Understand payer and provider data needs, navigate regulatory requirements, and learn the evolving business of healthcare.
- Flexible, Fully Online Format – 100% asynchronous coursework designed for working professionals. Study on your schedule without putting your career on hold.
- Career-Ready Skills – Communicate findings to non-technical stakeholders, drive data-informed decisions, and graduate prepared for analytical and leadership roles in healthcare.
Designed for working professionals
- Study on Your Schedule - 100% Online, Fully Asynchronous- No required class meeting times. No mandatory campus visits. Study when and where it works for you—early mornings, evenings, or weekends. Complete coursework around your job, family, and life commitments.
- Flexible Start Dates - Three start dates per year mean you don’t have to wait months to begin. Chose the term that aligns with your timeline.
- 18+ Month Completion - Complete all 32 credits in as few as 18 months, with a flexible schedule designed for working professionals.
- Weekly Time Commitment - Plan for 8-10 hours per week per course. Most students enroll in one to two courses per term, making the program manageable alongside full-time work.
- Classroom Connect Sessions - Join optional live, faculty-led virtual sessions to dive deeper into course material, discuss case studies, and connect with peers across the program. While attendance isn't required, these interactive sessions enhance understanding and strengthen your connection to the program community.
- Technology You Already Use - All you need is a computer and reliable internet connection. Access course materials through Northeastern’s learning management system from anywhere in the world.
What You'll Study
The program blends a robust analytics core with essential healthcare knowledge. You'll develop the tools and frameworks to extract meaningful insights from complex data—and communicate them to the people who need to act on them. Courses span healthcare data systems, applied statistics, data visualization, health informatics principles, and programming in R, SAS, and Python.
Graduates of this program will be equipped to:
- Analyze organizational and stakeholder challenges in healthcare settings—and develop data-driven solutions that improve patient outcomes
- Collect health data from diverse sources, ensuring accuracy and integrity
- Apply statistical, epidemiological, and data-mining methods using R, SAS, or Python to derive actionable insights
- Transform complex data into clear visualizations and charts that convey key findings to non-technical audiences
- Present analytical findings through concise, compelling narratives that drive decision-making
Where this degree takes you
Health data analytics and healthcare data science professionals are in high demand across hospitals, health systems, insurance companies, public health agencies, and health tech companies. Graduates of this program are prepared for roles including:
- Healthcare Data Analyst
- Clinical Informatics Specialist
- Data Scientist (Healthcare)
- Health Informatics Consultant
- Population Health Analyst
- Business Intelligence Analyst (Healthcare)
- Clinical Data Manager
- Health Information Manager/Director
- Healthcare IT Project Manager
- Chief Medical Information Officer (CMIO)
Admission pathways for all backgrounds
Skip the application - let your performance pave the way. With the Online MS in Health Data Analytics' Fast App pathway, you can skip the traditional application process and use your performance on two initial courses to secure your place in the program.
Complete two “pathway” courses (part of the required Analytics Core), get a ‘B’ grade or better, show proof of your bachelor’s degree by the time you complete the two courses, and you’ll join the next cohort in the full degree program.
⇒ Submit your Fast App to join the program today.
You can also apply to the program using the standard graduate application for direct admission consideration.
⇒ Learn more about Northeastern Online admissions and requirements.
Not ready for a full master's degree?
The Analytics Stack Track is a flexible, affordable way to earn your online analytics master’s degree at Northeastern—starting with a valuable credential at a reduced cost.
How it works:
Begin with the Online Graduate Certificate in Data Analytics Engineering, which covers the full analytics core required for three master’s programs:
- Online MS in Business Analytics
- Online MS in Data Analytics Engineering
- Online MS in Health Data Analytics
After completing the certificate, seamlessly apply your credits toward a master’s degree. Leverage earning your certificate while continuing into the master's program.
As an Analytics Stack Track learner, you’ll pay just $328 per credit for the certificate—significantly lowering the total cost of your master’s degree.
Current Fast App dates
Missed an enrollment deadline? Use the enrollment link in your email to enroll in the available term.
| Term | Submit app by | Enroll by | Start courses |
| Summer 2026 | April 1, 2026 | April 27, 2026 | May 6, 2026 |
Submit your Fast App to join the program today.
Not ready to start?
Get more information.
Analytics Hub Fast App Pathway Courses
Explore the Fast App Performance-Based pathway courses and review the course outlines to get a head start on your preparation before classes begin.
DADS 6400: Foundations for Data Analytics Engineering
Offers topics and skills designed to prepare students for advanced courses in data analytics engineering. Covers basic concepts and implementation of methods related to probability, eigenvalues and eigenvectors, cluster analysis, text mining, and time series analysis. Offers students an opportunity to learn how to work with modern data structures and apply computational methods for data cleaning and data wrangling operations.
DADS 6600: Computation & Visualization for Analytics
Offers students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. Covers basics of Python and R for data mining and visualization. Introduces students to static and interactive visualization charts and techniques that reveal information, patterns, interactions, and comparisons by focusing on details such as color encoding, shape selection, spatial layout, and annotation.
Get more info.
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