Data Science + Social Impact
DrivenData works on projects at the intersection of data science and social impact, in areas like international development, health, education, research and conservation, and public services. We want to give more organizations access to the capabilities of data science, and engage more data scientists with social challenges where their skills can make a difference.
In pursuit of these goals, DrivenData runs online machine learning competitions with social impact and works directly with mission-driven organizations to drive change through data science and engineering. We also maintain a number of popular open-source projects for the data science community, and have shared the prize-winning solutions from past competitions openly on GitHub for anyone to learn and build from.
We’ve worked with more than 80 organizations across 150+ projects, many of these made possible by the amazing efforts of the DrivenData community. Check out some examples below!
Public Health
Partners: Yelp, Harvard University, City of Boston
Combined Yelp data with Boston’s open data on past inspections to predict public health risks at restaurants. An algorithmic approach discovers 25% more violations.
Yelp Case Study →Conservation
Partners: Max Planck Institute for Evolutionary Anthropology, Arcus Foundation
Identified wildlife in video footage—automatically and at scale—by running a global algorithm development challenge and building an open source application with the winning solution.
Zamba Project Page →Development
Partners: IDEO.org, Bill & Melinda Gates Foundation, Airtel
Analyzed millions of mobile money records to uncover patterns in behavior, and then combined these insights with human-centered design to shape new approaches to delivering mobile money to low-income populations in Tanzania.
IDEO.org Case Study →In the press
What we do
DrivenData brings the transformative power of data science and AI to organizations tackling our world’s greatest challenges.
We find real world questions where data science can have positive social impact, then run online modeling competitions for data scientists to develop the best models to solve them.
To see what this looks like in action, read more about our process or check out our competitions!
Our partners
Impact-driven organizations are tackling hard questions where harnessing data can make a huge difference. But they often struggle to access the tools and the talent.
With the ability to access more and more data, organizations are looking for opportunities where data science and AI can help them advance their missions and operate more effectively. If this sounds like your organization, reach out to us or read more about how we work with organizations.
Our members
Data science professionals, students, and researchers are constantly on the lookout for interesting, real-world projects.
We engage experienced and aspiring data scientists to solve pressing problems for mission-driven organizations. Competitors get experience with real-world problems and a proven track record of results.
If that sounds like you, check our our information for data scientists, or jump right in and join a competition.
Updates from our blog
Advancing Data for Good
DrivenData Labs
Competitions aren't right for every problem. For more flexible needs or sensitive data sources, we have our own team of experienced data scientists and engineers to take the case.
Learn more about some of our recent projects and working with our team.
Reproducible data science
Since starting this platform, we’ve seen a lot of data science in the wild. As the field develops, it’s becoming increasingly important to organize data science work so that it’s easy to understand, reproduce, and build upon. We’ve done a lot of thinking, writing, and speaking on this topic.
Check out our (pithy) ebook on the 10 rules of reliable data science or try out our popular open source project structure: cookiecutter data science.
Ethical data science
We take our responsibility as stewards of data seriously, and we want to help others do the same. That's why we created an easy-to-use ethics checklist that can be integrated into any data science project. deon provides concrete, actionable reminders to help data scientists tackle critical discussions around issues like privacy, bias, and downstream impacts.
Try out our open source command line tool or learn from one of our practitioner workshops.
Join our mailing list
If you just want to hear about what's new with us follow us on twitter and sign up for our mailing list!
