Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY

From strategy to implementation: Putting data to work at USA for UNHCR

Friederike Schuur (Cloudera), Rita Ko (USA for UNHCR)
2:55pm–3:35pm Wednesday, 09/12/2018
Data-driven business management, Strata Business Summit
Location: 1E 10/11 Level: Non-technical
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Everyone will find value in this session.

What you'll learn

  • Learn how the Hive and Cloudera Fast Forward Labs transformed USA for UNHCR, during a time when there was an immediate need to maximize on the value derived from data to optimize their impact for refugees


In October 2015, Hungary closed its borders to refugees, a decision that alerted the world to the growing refugee crisis. USA for UNHCR helps save, protect, and rebuild the lives of refugees. The Hive, a special projects unit within USA for UNHCR, works hand-in-hand with partners around the globe in search of creative ways to support the work of USA for UNHCR.

Friederike Schuur and Rita Ko explain how the Hive and Cloudera Fast Forward Labs transformed USA for UNHCR, enabling the agency to use data science and machine learning (DS/ML) to address the refugee crisis. Along the way, they cover the development and implementation of a DS/ML strategy, identify use cases and success metrics, showcase the value of DS/ML, and detail new opportunities opened up by a showing of empathy (for instance, the US public donated record amounts to USA for UNHCR in response to Hungary’s border closure).

Data, data science, and machine learning can drive tangible value across a wide range of organizations, from for-profit to governmental and not-for-profit organizations. But these organizations struggle to put numbers and algorithms to good use. Friederike and Rita explain how to thoughtfully introduce and grow novel capabilities within an organization as large and as established as USA for UNHCR and outline strategies to help stakeholders recognize the value of a data-driven approach and create excitement for doing things in a different, data-driven way. Using the Hive as an example, you’ll learn the importance of a strategically crafted team identity through a careful selection of projects and thoughtful communication that allows the team to flexibly respond to current, changing demands while setting it up for long-term data science and machine learning success.

Friederike and Rita conclude by explaining how they built a network of trusted partners, advisors, and volunteers to engage in exciting projects given resource constraints common in a governmental or not-for-profit organization and reviewing recent data science and machine learning projects, such as tracking the development of refugee camps using satellite imagery (in collaboration with Stanford), born from a DataKind DataDive.

Photo of Friederike Schuur

Friederike Schuur


Friederike Schüür is a research engineer at Cloudera Fast Forward Labs, where she imagines what machine learning (ML) in industry will look like in the near-term future. She dives into new ML capabilities, builds prototypes that showcase state-of-the-art technology applied to real use cases, and advises clients on how to make use of new ML capabilities, from strategy to hands-on collaboration with in-house technical teams. Friederike is an advisor to a healthcare startup (in stealth mode) and a data science for social good volunteer with DataKind. She holds a PhD in cognitive neuroscience from University College London.

Photo of Rita Ko

Rita Ko


Rita Ko is the director of the Hive, the innovation lab at the UN Refugee Agency in the United States (USA for UNHCR), where she heads the application of machine learning and data science to explore new modes of engagement around the global refugee crisis. Her work in data science stems from her election campaign experience in Canada at the Office the Mayor in the City of Vancouver, where she successfully reelected Mayor Gregor Robertson three consecutive terms, and nationally on three election campaigns applying predictive modeling.