Mathematical Data Science is an exciting inter-disciplinary field that leverages Mathematics, Statistics and Computer Science to solve complex problems in business, medicine, sports management and many other fields.
Combining rigorous mathematical foundations with cutting-edge data science techniques, our Mathematical Data Science major empowers students to tackle complex problems and drive innovation forward. Applications close late March.
Our new major in Mathematical Data Science prepares students for careers in the rapidly expanding field of Data Science. This program offers students a unique blend of traditional data science skills and rigorous mathematical training. With a strong foundation in mathematical modeling and advanced statistical methods, students will develop and apply new algorithms to identify hidden patterns in large data sets and generate highly accurate predictions.
Beyond technical mastery, our graduates will also develop creative problem-solving skills, allowing them to approach data challenges with fresh perspectives. Whether analyzing large-scale datasets or developing new methodologies, our students will be equipped to stand out as leaders in the Data Science industry, driving data-driven discoveries and insights.
The Computational Data Science & Analytics track emphasizes the integration of core data analytics with advanced computing skills. This track covers a core of computer programming and machine learning courses which are complemented by courses in Mathematics and Statistics. This track is ideal for students whose goal is to work in the private sector as part of a Data Science team. A flow chart depicting the course requirements for the Computational Data Science & Analytics track are depicted here.
The Statistical & Mathematical Data Analytics track emphasizes mathematical and statistical theory alongside algorithmic development. This track is ideal for students seeking a strong mathematical foundation in preparation for graduate-level studies in mathematics. A flow chart illustrating the course requirements for the Statistical & Mathematical Data Analytics track is provided here.
There are numerous career opportunities in Data Science. A B.S. in Mathematical Data Science opens doors to a wide range of professions, including:
We encourage you to explore a range of career options to discover the best fit for your interests and skills.
The Mathematical Data Science major shares significant overlap with both the Computer Science and Mathematics majors. Adding a dual major should not significantly extend your graduation timeline, while also enhancing your competitiveness in future career opportunities. However, we strongly encourage students to consult with the Mathematics undergraduate advisor, John Zweibel, before committing to a dual major and review the Mathematical Data Science degree requirements in the Undergraduate Course Catalog.
Recent Ph.D graduate Dr. Luis Caicedo Torres’s research is in harnessing the power of scientific machine learning (Sci-ML) tools for modeling physical systems with low amount of data available or in systems with dynamics that are computationally infeasible. By drawing inspiration from classical partial differential equation techniques, he is working on building more robust systems that are able to accurately predict behavior in complex systems. In particular, Caicedo Torres is looking at the application of these ideas to neutron kinetics in subcritical nuclear systems and image recognition for nuclear safety applications. These style of systems are seeing an ever-increasing applicability throughout every area of science.
A student is considered "full-time" when enrolled in 15 credit hours. Students in our Mathematical Data Science major are expected to fulfill this requirement with a well-balanced selection of courses in Mathematics, Statistics, Computer Science and other disciplines. General education requirements are an essential component of an undergraduate degree and are best distributed evenly across all four years, ensuring a well-rounded and enriching academic experience. We encourage students to customize their degree to align with their individual academic interests and career aspirations.
It's normal to have questions or concerns when deciding your major. The faculty listed below are interested in helping you succeed in the Mathematical Data Science major at FIU. As the program designers they are fully equipped to address any concerns.
Ciprian G. S. Gal
Professor
305-348-1216
cgal@fiu.edu
DM 436B
Julian Edward
Professor
305-348-3050
edwardj@fiu.edu
DM 431C
John Zweibel
Associate Professor; Mathematics Undergraduate Advisor
305-348-3479
zweibelj@fiu.edu
DM 428
