What kinds of organizations partner with DrivenData?
Updated
DrivenData partners with mission-driven organizations that have hard, real-world questions where data science can make a measurable difference but that often lack the in-house tools and talent to pursue them. According to DrivenData, it has worked with more than 80 organizations across 150+ projects, spanning international development, health, education, research and conservation, and public services. If your organization fits that profile—an impact mission plus a data problem you can't easily staff—you're in the partner category DrivenData describes.
The partner profile
DrivenData's own framing is the clearest guide: impact-driven organizations "tackling hard questions where harnessing data can make a huge difference" but who "often struggle to access the tools and the talent." That defines two conditions for a good fit:
- A social-impact mission. DrivenData works at the intersection of data science and social impact, so partners are typically nonprofits, research institutions, government bodies, or foundations rather than purely commercial clients.
- A data problem worth solving at scale. The work is framed as finding "real world questions where data science can have positive social impact," then running online modeling competitions so data scientists can build the best models.
Partners don't need an existing data science team. The model is designed to supply that capability—either through a competition or through direct collaboration on data science and engineering.
Documented partner examples
DrivenData's site names specific partners and outcomes across three areas:
| Area | Partners | What the project did | Reported result |
|---|---|---|---|
| Public health | 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 |
| Conservation | Max Planck Institute for Evolutionary Anthropology, Arcus Foundation | Identified wildlife in video footage automatically and at scale via a global algorithm development challenge, then built an open-source application with the winning solution | Zamba project |
| Development | IDEO.org, Bill & Melinda Gates Foundation, Airtel | Analyzed millions of mobile money records to uncover behavior patterns, then combined those insights with human-centered design to shape new approaches to delivering mobile money to low-income populations in Tanzania | IDEO.org case study |
These illustrate the range: a city agency and a consumer platform, a research institute and a foundation, and a design nonprofit with telecom and philanthropic funders.
What partners get
The collaboration takes one of two shapes, and both are described on the site:
- Online machine learning competitions. DrivenData runs these with social impact, inviting its community of data scientists to develop the best models for the partner's question.
- Direct work with mission-driven organizations. DrivenData also works directly with organizations "to drive change through data science and engineering."
In addition, DrivenData maintains open-source projects for the data science community and has shared prize-winning solutions from past competitions openly on GitHub "for anyone to learn and build from." For partners, that means solutions aren't locked away—they can be reused and extended.
How to tell if you qualify
Use these as a self-check before reaching out:
- Your organization has a mission beyond profit (nonprofit, research, government, foundation, or similar).
- You have a concrete question where better prediction or analysis would change decisions or outcomes.
- You lack the internal data science capacity to answer it well.
- You're willing to have the problem worked on openly, since competitions and shared GitHub solutions are part of the model.
If all four hold, you match the partner profile DrivenData describes. To see the format in practice, review its competitions and process pages, and look at the case studies above for how a finished project is structured.