Data Science Program

The data science program at Saint Louis University offers an interdisciplinary curriculum supported by the departments of computer science and mathematics and statistics. Classes are small and taught by enthusiastic instructors.

About the Program

The ability to deeply analyze large and complex data sets is, and will continue to be, a valuable skill in industry, government and nonprofit sectors. The volume of data being collected and needing analysis has been growing rapidly, and there is no foreseeable end to the demand for students with strong analytical skills. Data science plays a unique role due to the nature of the discipline, as technical advances in the field support a broader aspect of Saint Louis University’s mission: “to work for the good of society as a whole.” While data is neutral, understanding it is central to a growing number of disciplines around the world.

Saint Louis University’s data science program is a joint effort between the departments of mathematics and statistics, and computer science. The degree is rigorous, with required advanced courses in both computer science and statistics. Students complete more than half of a mathematics major and more than half of a computer science major. The program includes two DATA-coded courses taken exclusively by data science students, a practicum taken twice (spring of freshman and sophomore years), and a yearlong senior capstone course.

Degrees

• Data Science, B.S.
• Data Science, B.S. to Bioinformatics and Computational Biology, M.S. Accelerated Program
• Data Science, B.S. to Computer Science, M.S. Accelerated Program
• Data Science, B.S. to Software Engineering, M.S. Accelerated Program
• Data Science, B.S. to Artificial Intelligence, M.S. Accelerated Program

Careers

Graduates have gone on to jobs in industry and government, such as:

• Microsoft
• Raytheon
• Girl Scouts of Eastern Missouri
• Boeing
• Textron Aviation
• NISA Investment Advisors
• Enterprise

Many students have also continued to graduate studies at institutions including Vanderbilt, Princeton, DePaul and Villanova.

Support

Data science students are assigned academic advisers who are faculty members in the department of mathematics and statistics. Academic support for lower-level math and computer science courses is available through math help sessions, the computer science tutoring center and university-wide academic support services. Students are encouraged to participate in both math club and computer science club activities.

Courses

For a complete list of the interdisciplinary courses offered in the data science program, check out the College of Arts and Sciences academic catalog.

DATA 1800 - Data Science Practicum I
A project-based course offering practical experience in the field of data science. Students work in teams on data science challenges that vary from semester to semester.

DATA 2800 - Data Science Practicum II
A project-based course offering practical experience in the field of data science. Students work in teams on data science challenges that vary from semester to semester.

DATA 4961 - Capstone Project I
The first part of a two-course sequence serving as a concluding achievement for graduating students, allowing them to apply knowledge that they have gained from the Data Science curriculum toward a year-long project.

DATA 4962 - Capstone Project II
The second part of a two-course sequence serving as a concluding achievement for graduating students, allowing them to apply knowledge that they have gained from the Data Science curriculum toward a year-long project.

Faculty

Darrin Speegle is the program director for the Department of Mathematics and Statistics at Saint Louis University. He joined SLU in 1997 and also serves as director of the Data Science Program. Speegle’s research interests include change point detection and dimension reduction.

Bryan Clair is a faculty member in the Department of Mathematics and Statistics at Saint Louis University. He joined SLU in 2000. His research interests include topology, combinatorics, Markov chains, latent class analysis and geospatial statistics.

Haijun Gong is a faculty member in the Department of Mathematics and Statistics at Saint Louis University. He joined SLU in 2012 and has multidisciplinary training in computational biology, statistics, machine learning, model checking and physics. His research focuses on developing and applying novel statistical inference and model checking techniques to study genetic networks and signaling pathways using high-dimensional omics data. In recent years, Gong has supported nine data science students through his NIH grants.

Jie Hou is a faculty member in the Department of Computer Science at Saint Louis University. He joined SLU in 2019. Hou’s research focuses on machine learning and data mining methods for bioinformatics. He develops data-driven computational approaches including machine learning, deep learning and computational optimization to address fundamental problems in the biological sciences, such as protein and RNA structure prediction.

Vahan Huroyan is a faculty member in the Department of Mathematics and Statistics at Saint Louis University. He joined SLU in 2024. His research interests include mathematical data analysis, machine learning, computer vision, distributed computing and probability theory.

David Letscher is a faculty member in the Department of Computer Science at Saint Louis University. He joined SLU in 2002. His research interests include computational topology.

Abby Stylianou is a faculty member in the Department of Computer Science at Saint Louis University. She joined SLU in 2019 and teaches CSCI 1070 Taming Big Data and CSCI 4710 Databases. Her research focuses on fine-grained image classification and image retrieval for various application domains, including plant science and efforts to combat human trafficking and child sexual abuse by identifying where victims are photographed.