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Information Management and Data Science Internship for Crisis Risk Analysis & Early Warning

  • UNDP New York USA (map)

UNDP’s Strategic Plan (2018-2021) recognizes the importance of contextual analysis, crisis prevention and recovery, and the management of multidimensional risks as fundamental for development.  The Crisis Bureau is responsible for UNDP's corporate crisis-related strategies, vision and priorities for crisis prevention, response, and recovery.  The Bureau supports policy and programme development in keys areas including Conflict Prevention and Peacebuilding, Rule of Law and Human Rights, Migration and Displacement, Livelihoods and Economic Recovery, and Disaster Risk Reduction and Recovery.

One of the areas of responsibility of UNDP’s Crisis Bureau is to ensure that UNDP is well positioned to anticipate and to respond in the timeliest and most effective manner to crisis, primarily regarding sudden onset crises and complex protracted crises, triggered by natural disasters or armed conflicts alike.  The Crisis and Fragility Policy and Engagement Team provides crisis risk and early warning support to HQ and to Country Offices (COs) to address their needs in contextual risk analysis, adaptation, early action and—acknowledging unique contextual circumstances as well as unique CO requirements—provide tailored support.

To improve UNDP’s crisis risk analysis capabilities, the Crisis Bureau is exploring the targeted use of data science to harness new and emerging technologies such as machine learning / artificial intelligence and alternative data sources such as social media analytics and satellite imagery analysis, to support forecasting collective risks to human development (including risks of disasters, impact of climate change, risk of violent conflict and social unrest) in order to inform preventive action to mitigate the potential effects of crises on affected populations.

In support of UNDP’s engagement on the use of data science for crisis risk analysis and early warning, the Crisis and Fragility Policy and Engagement Team is seeking an information management and data science intern to support the organization's early warning capacities, information gathering and management,  and the development of machine learning tools and competencies.

Duties and Responsibilities

The intern will provide support to the early warning team in its information management and data science tools development activities, particularly related to the further development and operation of the Crisis Risk Dashboard (CRD), which is a data management and visualization platform to track crisis risks.

Information management and tools development support may include:

  • Identifying additional data sources and manage data flows that support crisis risk analysis by engaging in data modeling and database development;

  • Supporting the collection, management, and publishing of documents, data, information, and digital content, using UNDP’s content management systems;

  • Developing customized applications and tools to strengthen CRD data collection, analysis and visualization capabilities;

  • Support the development of training material for the Global Crisis Risk Dashboard

  • Developing customized CRDs that offer country- or issue-based tracking and analysis by designing and developing visual interfaces, human-computer interaction modeling, and usability testing;

  • Researching innovative forms of acquiring data for early warning, particularly in context where data is scarce;

  • Contributing new ideas for improving the CRD in terms of the early warning data, and in terms of how the dashboard is used for effective crisis risk analysis;

  • Other related duties as may be assigned by the Early Warning Programme Specialist.

Machine learning / artificial intelligence tools development support may include:

  • Identifying new use cases for Machine Learning via Crisis Risk Dashboard applications

  • Supporting the development of machine learning models applying structured and unstructured learning including but not limited to regressions, random forest models, clustering models, sentiment analysis, NLP (natural language processing) and Topic Modelling

For more information and to apply, please click here.