Internship will take place at the University of North Florida campus, Jacksonville, FL. Both undergraduate and graduate students are welcome to apply for the internship. Please read the FAQs before submitting your application.
We are looking for students who aspire to be a data scientist to work as a DSSG Intern in a twelve-week internship program. Both undergraduate and graduate students are welcome to apply for the internship. Please read the FAQs before submitting your application.
2024 DSSG Internship ApplicationFL-DSSG Internship application is developed based on DSSG programs at Chicago and Washington.
We will re-open the application submissions in mid-January 2025.
We are no longer accepting DSSG Intern applications for summer 2024 program. Thanks for your interest with the FL-DSSG Program. Application process for summer 2025 internship program will open in mid-January 2025.
The DSSG program is an intensive, twelve-week summer internship experience. Students are placed on multi-disciplinary teams and matched with mentors to address real-world problems for our clients. FL-DSSG program is designed to train and strengthen data scientist workforce pipeline. The goal of the program is to give students an opportunity to solve a real problem in our community and to give local do-good agencies an opportunity to work with creative social trustees of knowledge. Students will receive valuable experience with data management, analysis, technology, and community needs as to prepare them for the workforce in STEM related fields.
For a truly interdisciplinary approach, student interns will work in teams that consists of expertise from several of the following areas: data mining, data visualization, geographic information systems, predictive modeling, programming, social policy, and statistical analysis. Mentors will have several years of experience with solving real world problems as well as creating social impact. Mentors will work closely with student teams on a project throughout the internship period. Project clients will demonstrate commitment to doing social good and will have mission focused on at minimum one of the following: education, environment, government services, health care, healthy living, safety/security, smart urban development, social & economic inequality, and sustainability.
Students who complete the FL-DSSG summer internship will receive a Florida Data Science for Social Good Internship Digital Badge issued by the University of North Florida. Earning FL-DSSG internship digital badge is indicative of the capability to work on data science projects that produce intended results, knowledge on data science best practices, engage in collaborative problem solving, work with cross-disciplinary teams, create intuitive and interactive visuals, and produce effective storytelling presentations.
To earn the FL-DSSG Internship badge, students must complete all the internship tasks, complete the assigned projects, deliver data science solutions to the project clients, submit final project reports, and make open-to-public presentations showcasing the project outcomes.
Please visit below links to learn more about FL-DSSG Internship Badge and UNF Digital Badging Initiative:
Note: FL-DSSG started issuing digital badges only in 2024. Thus, interns who completed the internship program prior to 2024 did not receive digital badges. Please see the respective year DSSG program pages for a listing of interns who completed the internship program.
The ability to affect change and do good in one’s community increasingly depends on having the right information at the right time to make the right decisions about things that are most important. Often, the information available to meet these needs are not well organized, not well understood, and not packaged in a way that helps those working in the community do their best.
Data Science for Social Good projects connect community expertise, data processing methods, computing power, and effective data visualization to help community organizations make data-based decisions to deal with wicked problems. A wicked problem is a vexing, persistent social or cultural issue that is complex in nature, interconnected with other problems, has policy implications, and requires many people working together to affect change. Data Science projects address wicked problems in one of several areas of societal importance, including education, the environment, government services, health care, healthy living, safety/security, smart urban development, social & economic inequality, and sustainability. DSSG Student Interns have the opportunity to contribute to projects that help solve these wicked problems in their communities.
The FL-DSSG Program is a 12-week summer internship program where small, interdisciplinary groups of students work with data science mentors (DSSG Sherpas) to complete projects that match data science expertise with real-world problems. Projects originate from community organizations who are trying to affect positive change in their communities and who have data management, analysis, and display projects that have the potential to shift understanding around a community issue, influence planning, revise practices, or see efforts in supporting community initiatives more focused or renewed.
Each year of the program, FL-DSSG Directors will solicit data science projects from community (non-profit) agencies. Once projects have been selected, the skills and abilities needed to help solve the data science problem are identified. Student DSSG Interns are then recruited to work in interdisciplinary teams during the summer to solve the data science problem. DSSG Sherpas (mentors) will work with the student teams to ensure the project is succeeding in its mission. DSSG Interns will work with knowledgeable leaders in the field, work on dynamic data science projects, and learn important professional and technical skills during the intensive internship program.
Student Interns will work closely with data science leaders and professionals on creative and impactful projects that serve a social good. DSSG Interns will be equipped with the skills, attitudes, and habits of data scientists, such as creative thinking in real-world settings, coding (e.g., R, Python, SQL, etc.), data analysis (data mining, multiple regression, probability), data visualization, and design-driven problem solving.