As data reshapes nearly every industry, the Katz School of Science and Health has launched an M.S. in Applied Statistics designed to train students to solve practical problems in finance, medicine, technology and artificial intelligence.
With total tuition of $19,000 for U.S. students—$35,000 for international students—the program ranks among the most affordable private master’s degrees in the country, offering a U.S. News Top 100 University education at a price comparable to many public institutions.
“The explosion of data has made statistical expertise more critical than ever,” said Marian Gidea, professor of mathematical sciences and director of the program. “Organizations today are drowning in data, but data alone is useless without people who know how to analyze it correctly and explain what it means. That is the gap this degree is designed to fill.”
Applied statistics turns raw numbers into clear, actionable insights that help people make informed decisions. Companies use it to forecast markets. Doctors rely on it to evaluate treatments. Technology firms apply it to improve artificial intelligence systems. By identifying patterns in data, statisticians help organizations make decisions grounded in evidence.
Demand for those skills is surging. The U.S. Bureau of Labor Statistics projects jobs for statisticians will grow 33 percent through 2030, far faster than most professions. Median salaries for those with a master’s degree approach $100,000, with even higher earning potential in fields such as quantitative finance and biotechnology.
“Our graduates will be prepared for careers that are not only well paid, but also meaningful,” said Gidea. “They will work on problems that affect health, economic stability and technological progress.”
The 30-credit, 10-course program is offered on campus in New York City and can be completed full time or part time. Students can pursue a general track or specialize in financial statistics, focused on quantitative finance and risk management, or biostatistics, which applies data science to medicine and public health.
Hands-on training is central to the program. Students analyze real datasets using industry-standard tools such as R and Python while learning how to test ideas, interpret results and clearly communicate their findings. They graduate with a professional portfolio built through capstone projects, internships or applied research, demonstrating their ability to turn data into solutions.
“Statistics is not just about getting the right answer,” said Gidea. “It’s about asking the right question, choosing the right method and explaining results in a way decision-makers can understand.”
