Data Science for Social Impact

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Since its founding, The Rockefeller Foundation has been a data-driven philanthropy focused on innovation and finding solutions to the world’s most pressing and persistent challenges.

Today, our Data Science for Social Impact team leverages research, analysis, funding, and partnering capabilities to ensure that the most advanced data science and machine learning tools are deployed in ways that empower underserved communities and increase equity.

To do this, we hold frequent convenings in order to build a network that brings together data scientists from across the field. We build products for internal teams within the Foundation, and we build trusted relationships with grantees. Across the U.S. and worldwide, we make early investments in young organizations and connect them with other partners. Our research helps us find people and organizations that have solved problems using data science. We work to apply those solutions to other problems like climate change and climate health.

Why it Matters

Innovation is critical to deal with a changing world, increasing sustainability, and equitably supporting human well-being.

>0GlobalGlobal
population lacks access to the internet [Brookings]
0%%
of organizations see data science as a key component furthering their digital innovations
~0Non-profitsNon-profits
and foundations are working in the data for social good space

Impact Stories

Want To Change Africa’s Future? For These Farmers, It Starts With a Tractor
Smallholder farmers in Africa are upping their productivity through an app that allows them to share tractors that are otherwise unaffordable.
Can Data Science Create Social Equity? These Nine Organizations Think So
Nine awardees offer examples of what data for social impact can look like when empowered with funding, technical assistance, and partnership.
Tackling Clean Water Advocacy, a Different Way: The Rise of BlueConduit
In high levels, lead poisoning can lead to anemia, brain damage, and a host of other health issues. For BlueConduit, eliminating lead services lines has been a guiding priority.
Mobilizing a Global Volunteer Network for Social Good
DataKind seems to have unlocked the key to enabling large-scale work on a budget.

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