Get ready! We're thrilled to announce that Data Science for Social Good Munich will be back in 2026!
We are moving full steam ahead with planning this incredible opportunity to apply data science to real-world social challenges. Mark your calendars: Registration is expected to open this winter.
Keep an eye on this page and our LinkedIn for updates on dates, projects, and application details as they become available. We can't wait to see you there!
Data Science for Social Good Munich is a fellowship dedicated to leveraging data science for impactful social change.
Held at the LMU Munich in Germany, the program selects talented data scientists from around the world to work on real-world projects for local social initiatives and non-profits.
Our mission is to create and sustain data-driven solutions for the greater good, fostering interdisciplinary teams with diverse skill sets and expertise. The project outcomes are diverse, ranging from descriptive analyses and interactive dashboards to robust machine learning models and data infrastructure.
DSSGx Munich is proudly hosted by the Department of Statistics at LMU Munich and funded by the Munich Center for Machine Learning (MCML).
Data Science for Social Good (DSSG) is an initiative founded at the University of Chicago in 2013 (learn more). Its mission is to create and sustain programs + solutions + communities that enhance the use of data science + AI for social good. From the very beginning, the flagship project of DSSG has been its annual fellowship program, where aspiring data scientists can sharpen their skills in machine learning & data science while working on real problems for the social good. Since 2023, the department of statistics at LMU Munich and the Munich Center for Machine Learning (MCML) are hosting a local branch of the DSSG fellowship program in Munich.
Our vision is to have interdisciplinary teams with diverse backgrounds and skillsets joining forces for meaningful projects. We believe in a strong added value of collaborations across many academic disciplines
Outcomes of the projects are not limited to machine learning models, but can be dashboards, insights, descriptive analyses or even data pipelines and infrastructure
Sponsors and Affiliated Organisations:
If you have any questions, concerns, feedback or anything is unclear to you, feel free to reach out to us at dssgx@stat.uni-muenchen.de.