Master of Science in Data Science and Statistics

��Ƶ's STEM-designated Master of Science in Data Science and Statistics program trains future leaders to meet the growing demand for data-informed decision-making in the era of artificial intelligence and machine learning. Previously known as the MA in Statistics (before Fall 2025), this innovative program bridges the gap between the academic rigor and the dynamic demands of the modern world. By integrating a robust mathematical and statistical foundation, cutting-edge computation techniques and real-world applications, our curriculum ensures that graduates are not just adept at statistical theory but are also skilled in applying insights to solve contemporary challenges. Courses in the program feature real-world projects, where students engage directly in advanced data science practices, preparing them for the professional challenges of industry and beyond.

The MS in Data Science and Statistics program requires ten 4-credit courses in statistics and data science, to be finished in two years or as soon as three regular semesters. The capstone seminar focuses on integrating knowledge from various courses through practical projects and presentations, emphasizing critical thinking and problem-solving skills. An exit exam or final thesis is not required. See the Curriculum page for the degree requirement and the course catalog.

For Binghamton's undergraduate students, the Department offers a 4+1 degree program which combines a BA/BS degree in Mathematical Sciences with the MS degree, allowing students to complete both degrees in five years.

Why Data Science: By the Numbers

#3 best occupation in the U.S., according to Glassdoor (2022)
#4 fastest growing occupation in the U.S., according to Bureau of Labor Statistics
$108,020, median pay in the data science field, according to the Bureau of Labor Statistics
$242,900, median salary of highly experienced data science managers, according to the Burtch Works Salary Report (2023)

Professional Development

The MS in Data Science and Statistics program provides students with a strong practical foundation for careers in both the public and private sectors. Faculty offer close guidance and support throughout the program, fostering an immersive and collaborative learning environment. Professional development is built into the curriculum through applied courses like Practical Data Analysis and the Capstone Project. Students also stay current with emerging trends by attending departmental seminar series in statistics, data science, and applied machine learning, featuring leading researchers from academia and industry.

After You Graduate

Graduates of the MS in Data Science and Statistics program are well-prepared for careers in industry, government, and research. The demand for professionals with advanced data skills continues to grow rapidly—according to the U.S. Bureau of Labor Statistics, employment of data scientists is projected to increase by 35% from 2022 to 2032. Our alumni pursue roles such as data scientists, statisticians, analysts, quantitative researchers, machine learning engineers, and professionals in fields like finance, healthcare, technology, and public policy.

Why Binghamton's MS in Data Science & Statistics Program?

With 100% of instruction by research-active faculty and total in-state tuition starting at just $15,078, our program delivers elite academic quality without the elite price tag.

By the Numbers

#1 SUNY in best salaries — Wall Street Journal's "America's Best Colleges," 2025
16-21 months — Program can be completed in as few as 16 months (three semesters) or within four semesters for most students.
100% of the instruction is delivered by tenured/tenure-track faculty
$15,078-$18,846 total tuition — for New York residents, depending on whether the program is completed in three or four semesters. See the tuition and financial aid details page.

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Who Should Apply?

The MS in Data Science and Statistics program is designed for individuals with strong quantitative backgrounds who aim to enhance their skills in data science and statistical methods. Ideal applicants have completed undergraduate coursework in calculus (at least two semesters), linear algebra, and probability and statistics. Degrees in STEM fields or quantitatively oriented disciplines such as economics or management are preferred. Familiarity with programming languages like R or Python is also beneficial (see the Computing Preparation page). Prospective students should review the program prerequisites and application details for more information.