Engineering Science (Data Science) MS

1 Year On Campus Masters Program

University at Buffalo SUNY

Program Overview

The Master of Science in Engineering Science with a focus in Data Science at the University at Buffalo provides students with advanced knowledge of big data, computational methods, and analytical techniques. Designed primarily for students with engineering, natural science, or mathematical science backgrounds, the programme combines theoretical foundations with practical training in data collection, data management, statistical learning, machine learning, and scalable data-driven discovery.

Curriculum Structure

The programme requires 30 credit hours, consisting of 18 credits of core courses, 6 credits of electives, a 3-credit data science survey course, and a 3-credit project or capstone. It follows a cohort-based structure, with students progressing through core courses before completing specialised electives and an applied project.

First Semester – Data Science Foundations

Students build their mathematical, statistical, and programming foundations through courses such as Introduction to Probability Theory for Data Science, Introduction to Numerical Mathematics for Computing and Data Scientists, Statistical Learning and Data Mining I, and Programming and Database Fundamentals for Data Scientists. These subjects introduce probability theory, numerical methods, statistical learning, programming, and database fundamentals.

Second Semester – Advanced Data Analytics

Students develop advanced analytical skills through Statistical Learning and Data Mining II, Introduction to Machine Learning, and Data Models Query Language, along with an elective. Topics include supervised and unsupervised learning, clustering, regression, machine learning algorithms, database structures, and query languages.

Third Semester – Applications and Project Work

Students complete the Data Science Survey Course, which explores applications of data science in areas such as bioinformatics, health informatics, engineering, finance, and data ethics. They also complete a 3-credit data science project, which may involve an industry internship, faculty-supervised research, or an experiential project addressing an industry problem.

Focus Areas

Data Science, Big Data Analytics, Statistical Learning, Data Mining, Machine Learning, Predictive Analytics, Computational Mathematics, Probability Theory, Statistical Analysis, Programming, Database Management, Data Modelling, Scalable Data Analytics, Data Engineering, Deep Learning, Reinforcement Learning, Data Visualisation, Bioinformatics, Health Informatics, Financial Data Analytics.

Learning Outcomes

Students develop the ability to collect, manage, process, and analyse large datasets using mathematical, statistical, and computational techniques. They learn to apply supervised and unsupervised machine learning methods, build predictive models, manage databases, and use programming tools to extract meaningful insights. The programme also strengthens their ability to solve complex data-related problems through independent projects, industry experience, and interdisciplinary applications.

Professional Alignment (Accreditation)

The programme is officially registered with the New York State Education Department and is STEM-approved. Eligible international graduates may qualify for the 24-month STEM Optional Practical Training extension, subject to U.S. immigration requirements. The official programme information does not identify a separate professional accreditation specifically for this degree.

Reputation (Employability Rankings)

The University at Buffalo's Institute for Artificial Intelligence and Data Science offers this programme with an emphasis on practical data science and computing skills. Students benefit from opportunities to complete industry-based internships, faculty-supervised research, and collaborative projects addressing real-world data challenges. The official programme page does not publish a specific programme-level employability ranking, graduate employment rate, or average salary.

Programme Details

Degree Awarded: Master of Science (MS)
Specialisation: Engineering Science – Data Science
Total Credits: 30 credit hours
Programme Duration: 1–1.5 years
Study Mode: In-person
Study Options: Full-time and part-time
STEM Designation: Yes
Intakes: Fall and Spring
Practical Component: Data science project, faculty-supervised research, or eligible industry internship
Target Background: Engineering, Natural Sciences, Mathematics, or related quantitative disciplines

Experiential Learning (Research, Projects, Internships etc.)

At the University at Buffalo, the MS in Engineering Sciences with a focus on Data Sciences is designed to provide students with a robust blend of theoretical knowledge and practical skills. The program emphasizes experiential learning, allowing students to engage in hands-on projects, collaborate with peers, and utilize state-of-the-art facilities and tools. This approach not only enhances your understanding of data science concepts but also prepares you for real-world challenges in the field.

Here are some key aspects of the experiential learning opportunities available in this program:

- Research Laboratories: Access to specialized labs such as the Data Science Research Center, where you can work on cutting-edge projects and collaborate with faculty on innovative research.

- Software and Tools: Proficiency in industry-standard software such as Python, R, MATLAB, and SQL, along with tools like Tableau for data visualization and machine learning frameworks.

- Group Projects: Engage in collaborative projects that simulate real-world data science problems, fostering teamwork and communication skills essential for your future career.

- Internship Opportunities: The program encourages internships with local and national companies, providing invaluable experience and networking opportunities in the data science industry.

- Field Trips: Participate in field trips to tech companies and research institutions, gaining insights into the latest industry trends and practices.

- Libraries and Resources: Utilize the extensive resources at the UB Libraries, including access to databases, journals, and research materials specifically tailored for engineering and data science.

- Institutes and Centers: Collaborate with the Center for Computational Research and the Institute for Artificial Intelligence and Data Science, which offer additional resources and expertise.

These experiential learning components are designed to ensure that you not only learn the theoretical aspects of data science but also apply them in practical settings, making you a well-rounded candidate for future employment.

Embarking on this journey in the MS Engineering Sciences in Data Sciences program will equip you with the skills and experiences necessary to thrive in the dynamic field of data science. I encourage you to apply and take the next step toward your future!

Progression & Future Opportunities

The MS in Engineering Sciences with a focus on Data Sciences at the University at Buffalo SUNY prepares graduates for a dynamic career in a rapidly evolving field. Alumni have successfully secured roles such as Data Scientist, Machine Learning Engineer, and Business Intelligence Analyst, showcasing the program's strong alignment with industry needs. With a solid foundation in data analysis and engineering principles, graduates are well-equipped to tackle complex challenges in various sectors:

- University Services for Employment: The Career Services office offers personalized career counseling, resume workshops, and interview preparation to help students stand out in the job market. Additionally, the Engineering Career Fair connects students directly with leading employers in the tech and engineering sectors.

- Employment Stats and Salary Figures: According to recent data, graduates from the program have a high employment rate, with over 90% securing jobs within six months of graduation. The average starting salary for graduates in data science roles is around $85,000, with potential for significant growth as they gain experience.

- University–Industry Partnerships: The University at Buffalo has established partnerships with major companies like IBM and Microsoft, providing students with opportunities for internships, collaborative projects, and networking events that enhance their practical experience and employability.

- Long-term Accreditation Value: The program is accredited by the Accreditation Board for Engineering and Technology (ABET), ensuring that the curriculum meets high standards of quality and relevance in the engineering field, which is recognized by employers globally.

- Graduation Outcomes: Graduates have gone on to work at prestigious organizations such as Google, Amazon, and Deloitte, demonstrating the program's effectiveness in preparing students for successful careers.

Further Academic Progression: After completing the MS in Engineering Sciences in Data Sciences, students have the option to pursue a Ph.D. in Engineering or Data Science, allowing them to delve deeper into research and contribute to advancements in the field. This path can lead to academic positions or specialized roles in research and development within industry settings. Additionally, graduates may choose to obtain professional certifications in data analytics or machine learning to further enhance their expertise and career prospects.

Choosing this program at the University at Buffalo SUNY is a strategic step toward a fulfilling and prosperous career in data sciences.