
We’re training data scientists to tackle problems that really matter.
We’re not running the Data Science for Social Good Summer Fellowship in Pittsburgh in 2023 and plan to run it again in 2024
You can still apply for full-time positions including post-doc fellows, research scientists, and a software engineer for our year-round Data Science and Public Policy team at CMU across the Machine Learning Department and Heinz College of Public Policy
Join our mailing list to get updates and to attend our events this summer.
The Data Science for Social Good Fellowship is a full-time summer program to train aspiring data scientists to work on machine learning, data science, and AI projects with social impact in a fair and equitable manner. Working closely with governments and nonprofits, fellows take on real-world problems in education, health, criminal justice, sustainability, public safety, workforce development, human services, transportation, economic development, international development, and more.
For three months they learn, hone, and apply their data science, analytical, and coding skills, collaborate in a fast-paced atmosphere, and learn from full-time mentors coming from industry and academia.
The Summer Fellowship

The 2022 program brought 24 aspiring data scientists from across the world to Carnegie Mellon University. They are current (or recent) graduate and undergraduate students from quantitative and computational fields – from computer science and machine learning, to statistics, math, physical sciences and engineering, to social sciences, public health and public policy.
From June until end of August, they worked in teams of 3-4 on data science projects in partnership with nonprofits and government agencies, to tackle data-intensive high impact problems in education, public health, public safety, transportation, criminal justice, environmental issues, city operations, and social services, learning from full-time experienced mentors and project managers.
News
Tackling Tenant Harassment in New York City: A Data-Driven Approach
Jerica Copeny, Samantha Fu, Rebecca Johnson, and Teng Ye Tackling Tenant Harassment in New York City: A Data-Driven Approach This [...]
Data Science for Social Good Announces 2018 Projects in Chicago and Lisbon
2018 Data Science for Social Good Goes Global, Tackling Diabetes, Tenant Harassment, Unemployment, and More Fellows in Chicago and Portugal [...]
Human Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville
Human Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville This is the third in our three-part series “Lessons [...]
Tech Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville
Tech Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville This is the second in our three-part series “Lessons [...]
Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville
Lessons Learned Implementing Early Intervention Systems in Charlotte and Nashville, Part 1 From the company’s creation, Netflix has relied on [...]
Representativeness Analysis: How Our Data Reflects the Real Labor Market Dynamics
Representativeness Analysis: How Our Data Reflects the Real Labor Market Dynamics This month, we will discuss the representativeness of Data@Work [...]