About DrivenData

DrivenData brings the transformative power of data science and AI to organizations tackling the world’s biggest challenges. We run online machine learning challenges with social impact, and we work directly with mission-driven organizations to drive change through data science and engineering.

Since 2014 we’ve worked with more than 80 organizations across 150+ projects in areas like international development, health, education, research and conservation, and public services. We're a team of smart, passionate data scientists and engineers interested in doing good work for good reason. If you're interested in our current job opportunities, check out our careers page.

Meet the team

Peter Bull

Co-founder
Data science and engineering

Peter holds a master's in Computational Science and Engineering from Harvard’s School of Engineering and Applied Sciences. He previously worked as a software engineer at Microsoft and earned a BA in philosophy from Yale University where he met Greg.

Christine Chung

Senior Data Scientist
Data science and engineering

Christine holds a master's in Computational Analysis and Public Policy from the University of Chicago, where she served as a Mayoral Fellow with the City of Chicago. She previously worked as a data scientist and machine learning engineer for Meetup. She earned her BA in Social Thought and Political Economy from the University of Massachusetts at Amherst.

Justin Chung Clark

Data Scientist
Data science and engineering

Justin holds a master's in Data Science from Harvard’s School of Engineering and Applied Sciences. He previously worked as a data scientist and software engineer doing tech policy research at the Berkman Klein Center at Harvard University. He earned a BA in International and Global Studies from Brandeis University.

Emily Dorne

Lead Data Scientist
Data science and engineering

Emily holds a master's in International Development from The New School and a data science certificate from Metis. She previously worked at the Bill & Melinda Gates Foundation, Stanford Center for International Development, and Brookings Institution. She graduated summa cum laude from Washington University in St. Louis.

David Flasterstein

Data Scientist
Data science and engineering

David holds a master's in Computer Science and a bachelor's in Political Science from Washington University in St. Louis. Before DrivenData, he was a machine learning engineer at Amazon where he helped train and evaluate machine learning models to classify billions of product images. He has also worked as a legislative assistant in the Washington State Legislature.

Robert Gibboni

Senior Data Scientist
Data science and engineering

Robert holds a PhD in Neuroscience from the University of California, Berkeley. He previously worked on experimental and computational approaches to brain decoding from functional magnetic resonance imaging data. He graduated summa cum laude from the University of Arizona in 2009.

Jackie Glasheen

Data Scientist
Data science and engineering

Jackie holds a master's in Computational Analysis and Public Policy from the University of Chicago. She previously worked as a data scientist and researcher at the US Census Bureau, a senior data analyst at Toast, and an economist at Compass Lexecon. She earned her BA in Economics from Boston College.

Chris Kucharczyk

Senior Data Scientist
Data science and engineering

Chris holds a B.S. in Physics with Honors and Distinction from Stanford University and a Ph.D. in Materials Science from the California Institute of Technology where he studied solid oxide fuel cell catalysts. Prior to DrivenData, Chris worked at IDEO and IDEO.org at the intersection of data science and human-centered design.

Greg Lipstein

Co-founder
Business development

Greg holds an MBA from Harvard Business School. He has previous experience working as a management consultant at Bain & Company and in market development at green-tech startup Blu Homes. Greg served with Teach for America for two years, after graduating summa cum laude from Yale University in 2008.

Hannah Moshontzde la Rocha

Senior Program Manager
Program management

Hannah holds a PhD in Psychology from Duke University and received postdoctoral training at the University of Wisconsin Madison. She has led and managed behavioral science research projects at the Center for Open Science and the Psychological Science Accelerator, and previously worked as a data scientist at Hunt Club. She holds a BA in Psychology from Reed College.

Jay Qi

Lead Data Scientist
Data science and engineering

Jay holds a master's in Mechanical Engineering from the California Institute of Technology, where he studied computational fluid dynamics and optimal flow control. Before DrivenData, he was a lead data scientist at Uptake, where he used machine learning to predict failures of industrial machines. He earned a B.S.E. in Mechanical and Aerospace Engineering from Princeton University.

Isha Shah

Data Scientist
Data science and engineering

Isha holds a bachelor's degrees in Neuroscience and Economics from Barnard College and a master's degree in Computer Science at Columbia University. She previously worked as a research analyst at the Brookings Institution on local economic and workforce development and in the antitrust division of NERA Economic Consulting.

Isaac Slavitt

Co-founder
Data science and engineering

Isaac holds a master's in Computational Science and Engineering from Harvard’s School of Engineering and Applied Sciences. He holds a BS in Operations Research from the U.S. Coast Guard Academy, and spent seven years as a Coast Guard officer serving in a variety of operational and quantitative roles.

Katie Wetstone

Senior Data Scientist
Data science and engineering

Katie holds a Master of Development Practice from the University of California, Berkeley, where she focused on data science for social good. Previously she worked with the Human Rights Campaign, Americorp’s American Conservation Experience, and the White House Office of Science and Technology Policy. She earned a BA in chemistry with high honors from Harvard University in 2015.

Our real-world impact

All projects
Partners: Max Planck Institute for Evolutionary Anthropology, Arcus Foundation, WILDLABS

Automating wildlife identification for research and conservation

Detected wildlife in images and videos—automatically and at scale—by building the winning algorithm from a DrivenData competition into an open source python package and a web application running models in the cloud.

Partners: Private sector, social sector

Building LLM solutions

Built solutions using LLMs for multiple real-world applications, across tasks including semantic search, summarization, named entity recognition, and multimodal analysis. Work has spanned research on state-of-the-art models tuned for specific use cases to production ready retrieval-augmented AI applications.

Partners: The World Bank, The Conflict and Environment Observatory

Identifying crop types using satellite imagery in Yemen

Used satellite imagery to identify crop extent, crop types and climate risks to agriculture in Yemen, informing World Bank development programs in the country after years of civil war.

Partners: IDEO.org

Illuminating mobile money experiences in Tanzania

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.

Partners: Insecurity Insight, Physicians for Human Rights

Tracking attacks on health care in Ukraine

Built a real-time, interactive map to visualize attacks on the Ukrainian health care system since the Russian invasion began in February of 2022. The map will support partner efforts to provide aid, hold aggressors accountable in court, and increase public awareness.

Partners: CABI Plantwise

Mining chat messages with plant doctors using language models

Automated recognition of agricultural entities (such as crops, pests, diseases, and chemicals) in WhatsApp and Telegram messages among plant doctors, enabling new ways to surface emerging trends and improve science-based guidance for smallholder farmers.

Partners: Data science company foundation

Matching students with schools where they are likely to succeed

Used machine learning to match students with higher education programs where they are more likely to get in and graduate based on their unique profile, with a focus on backgrounds traditionally less likely to attend college or apply to more competitive programs.

Partners: Fair Trade USA

Mapping fair trade products from source to shelf

Visualized the flow of fair trade coffee products from the farms where they are grown to the stores where they are sold, connecting the nodes in supply chain transactions and increasing transparency for customers and auditors.

Partners: The World Bank, Angaza, GOGLA, Lighting Global

Developing performance indicators and repayment models in off-grid solar

Analyzed repayment behaviors across dozens of pay-as-you-go (PAYG) solar energy companies serving off-grid populations throughout Africa, and developed KPIs to facilitate standardized reporting for PAYG portfolios.

Partners: Haystack Informatics

Modeling patient pathways through hospitals

Mapped out the probabilistic patient journeys through hospitals based on tens of thousands of patient experiences, giving hospitals a better view into the timing of the activities in their departments and how they relate to operational efficiency.

Partners: Yelp, Harvard University, City of Boston

Predicting public health risks from restaurant reviews

Flagged public health risks at restaurants by combining Yelp reviews with open city data on past inspections. An algorithmic approach discovers 25% more violations with the same number of inspections.

Partners: Education Resource Strategies

Smart auto-tagging of K-12 school spending

Built algorithms that put apples-to-apples labels on school budget line items so that districts understand how their spending stacks up and where they can improve, saving months of manual processing each year.

Partners: Love Justice

Building data tools to fight human trafficking in Nepal

Aided anti-trafficking efforts at border crossings and airports by combining data across locations and surfacing insights that give interviewers greater intelligence about the right questions to ask and how to direct them.

Partners: GO2 Foundation for Lung Cancer

Putting AI into the hands of lung cancer clinicians

Translated advances in machine learning research to practical software for clinical settings, building an open source application through a new kind of data challenge.

Partners: Microsoft

Driving data education through custom competitions

Developed online, white-label data science competitions for students to synthesize their learnings and test their skills on applied challenges. Each capstone features a real-world dataset that focuses on an important issue in the social sector.

Work with us to build a better world

Learn more about how our team is bringing the transformative power of data science and AI to organizations tackling the world's biggest challenges.