Undergraduate Data Science Immersion

Vanderbilt Data Science offers opportunities to help support immersion experiences for undergraduates.

Connecting with Student Talent

If you have research projects that you would like to advertise and promote to Vanderbilt students, please visit this page for information. Here you can learn more about connecting with students who have computational, quantitative, and data science interests.

Research Immersion in Data Science

Data science is an emerging interdisciplinary field whose goal is to extract knowledge and enable discovery from complex data using a fusion of computation, mathematics, statistics, and machine learning. Datasets can be as varied as maps of the universe, MRI images, human genomes, medical records, stock market transactions, educational data, historical texts, infrastructure systems, or website clickstream data.

Over the coming decades, data science is expected to have significant impacts on basic and applied research in the sciences, social sciences, arts and humanities, and engineering as well as impact all sectors of the economy from health care to education, government, transportation, finance, manufacturing, construction, and urban planning.

  • Data science has the potential to improve individual and community health and education
  • Develop smart communities that enable efficient circulation of people, goods, and services
  • Enable informed decision making in public and private sectors
  • Enhance environmental sustainability and overall quality of life

Given the wide range of applications and potential benefits, the powerful tools and techniques of data science must be used ethically and responsibly.

  • About Research Immersion

    Research Immersion in Data Science can be completed during the academic year or over the summer. Summer research can come in a variety of forms, including summer fellowships through the VUSRP, an NSF REU, of the Data Science Institute Summer Research Program (DSI-SRP).

    Students engaged in research immersion in data science can conduct research under the mentorship of a faculty member on a range of topics, including

    • Foundational data science, which involves the development, evolution, or implementation of data science methods
    • Application of data science techniques, methods, and tools to one or more fields in the physical, life, or social sciences, engineering, arts, or humanities
    • The study of the impact of data on society and its institutions
  • Student Preparation

    To prepare for a research immersion in data science, students are encouraged to take at least one semester of computer programming (DS 1100, CS 1100, 1101, or 1104) and at least one semester of statistics (various options across many departments) in their first year or sophomore year. Students may also need to take other coursework relevant to the research immersion topic in consultation with the faculty mentor.

  • Requirements for Completion

    To satisfy research immersion in data science, you must complete the following components:

    1. Research Experience (Academic Year or Summer Option)

    • Summer Research Experience Option
      Complete a full-time (40 hours per week) summer research experience in a laboratory of at least 10 weeks in duration. For example, DSI-SRP, VUSRP, NSF REU, other formal summer research program, or full-time paid or full-time volunteer summer research assistantship.


    • Academic Year Research Experience Option
      Complete a course related to data science that provides suitable training for the chosen research direction (at least 3 credit hours); the introductory computer programming course and introductory statistics course cannot count towards this requirement. Complete at least 6 credit hours of undergraduate research in data science.

    2. Communication of Research

    • Write a 15-page (minimum) research paper related to the research project.


    • Give an oral presentation of the research project at a poster session (e.g., the Vanderbilt Undergraduate Research Fair or a regional, national, or international conference) (submit an electronic version of the poster) and write a 5-page (minimum) summary and reflection of the research project.

Data Science for Social Good Immersion Project

The Data Science for Social Good (DSSG) program is a ten-week, full-time summer internship immersion experience where participants work as part of a data science team on a pre-selected project for a not-for-profit organization, Vanderbilt group, or government organization.

  • About DSSG

    The DSSG teams will be led by a DSI staff Data Scientist and the immersion experience will be co-mentored by a full-time Vanderbilt faculty member. The project will require close collaboration with the partner organization, participation in weekly planning sessions, and weekly presentations on current work (demos). In addition, participants will be able to attend weekly workshops on essential skills and tools for data scientists.

    In the event that there are multiple Social Good projects, interns will be able to rank their preference, and assignments will be made based on project needs, intern skills, and preference.

  • Application Information

    As part of the applications, students will be asked to describe their programming, statistics, and machine learning experience (if any). While all levels of experience will be considered, particular projects may require particular skills. To prepare for this immersion experience, other data science immersion experiences, and a number of other immersion experiences, we recommend that students have taken at least one semester of computer programming (CS/DS 1100, CS 1101, or CS 1104) and at least one semester of statistics (various options across many departments) in their first year or sophomore year. The new Data Science Minor is also excellent preparation for this and other immersion experiences.

  • Requirements for Completion

    For the DSSG to count towards immersion, students must complete the following:

    • 10 weeks of full-time (40 hours per week) summer work on a DSSG project.
    • Attend all announced summer workshops and meetings.
    • A final product agreed upon with your faculty immersion coordinator and DSSG faculty co-mentors, which could be (a) A 15-page (minimum) research paper, (b) An oral presentation or poster of the work plus a 5-page (minimum) summary and reflection of the research project, or (c) another products agreed upon and documented.

More information about the DSSG and the application process can be found here.

Students interested in the Data Science for Social Good Internship (and using the experience for immersion) are encouraged to contact Jesse Spencer-Smith at jesse.spencer-smith@vanderbilt.edu, Chief Data Scientist for Vanderbilt Data Science.

Internship with Vanderbilt Data Science

Vanderbilt Data Science (VDS) offers an internship opportunity for immersion through the Data Science Trainee Program (DSTP).

DSI trainees will work with its professional staff of data scientists on a range of projects, developing a working knowledge of data science technical topics, building experience with organizing and executing data science projects, and consulting with potential clients for data science projects.

  • About DSTP

    The DSTP currently has two tracks, each one semester long:

    Data Science Project Management Track : In the role of Scrum Assistant, trainees will ensure the progress of ongoing DSI projects by organizing work and scrum tasks for each Agile sprint cycle of work to meet project goal; trainees will ensure the coherence and management of data science projects using industry-standard tools.

    Data Science Code Contributor Track: In the role of Code Contributor, trainees apply programming skills in R or Python using machine and deep learning techniques on a DSI engagement during the semester. Students engage in Agile meetings for approximately 3 hours per week, and are expected to use industry-standard tools including git and GitHub, collaboratively contribute to the code repositories using pull requests and other tools, and use computational infrastructure including ACCRE as the project requires. Students may acquire these skills from DSI workshops taken during the course of the Program or prior to the program based on the constraints of the engagement.

  • Application Information

    Students are accepted into the DSTP at the beginning of each semester (Fall, Spring, Summer) and applications will be reviewed on a rolling basis in the 4 weeks surrounding the beginning of the semester until capacity is reached, based on the availability of positions. Students interested in the Data Science Trainee Program are invited to contact Charreau Bell, Senior Data Scientist (charreau.s.bell@vanderbilt.edu) prior to the beginning of each semester. Students interested during the middle of the semester are encouraged to take the Skills Training DSI workshops in preparation for the upcoming semester of application.

  • Requirements for Completion

    To earn credit for immersion, students will need to complete two trainee program tracks, where the Project Management Track may be pursued only once. Students will also need to work with the DSI team, DSI faculty mentors, and faculty immersion coordinator on a designated final project related to their data science experience (it could be a paper, a presentation, some tangible deliverable, or something else entirely).

Faculty mentors for this immersion experience will be Jesse Spencer-Smith, Chief Data Scientist and Adjunct Assistant Professor of Computer Science (jesse.spencer-smith@vanderbilt.edu), and Charreau Bell, Senior Data Scientist and Director of the Undergraduate Data Science Minor (charreau.s.bell@vanderbilt.edu).