Data Scientist

The United Nations Office for the Coordination of Humanitarian Affairs (OCHA) has a Centre for Humanitarian Data in The Hague, the Netherlands which is focused on increasing the use and impact of data in the humanitarian sector. The vision is to create a future where all people involved in a humanitarian emergency have access to the data they need, when and how they need it, to make responsible and informed decisions. The Centre has four workstreams: data services (managing the Humanitarian Data Exchange platform), data responsibility, data literacy and predictive analytics.

An area of emerging interest in the humanitarian sector is data science and predictive analytics: asking what will happen in a particular humanitarian context and using machine learning and the application of statistical modelling to arrive at an answer. The Centre initiated its work on predictive analytics through our 2018 and 2019 Data Fellows Programme, and has continued to invest in this area through research into the development of models related to different aspects of humanitarian response. In September 2019, the Centre created a workstream for predictive analytics with a focus on three areas: model development, a peer review process for partner models, and community and capacity building. More recently, the Centre’s predictive analytics team has supported OCHA’s anticipatory action frameworks in a dozen countries, enabling humanitarian organizations to get ahead of shocks and mitigate their impact.

Purpose and Scope of Assignment

The Centre is seeking to recruit a Data Scientist who has the skills and experience to assess available models, develop new models and generate recommendations for their use in anticipatory action. We are looking for a candidate who is familiar with the analytical methods used in the humanitarian sector, and can think strategically about how to use data to create value for crisis response. The right candidate has the skills and abilities to develop analytical models designed to turn data into action. They should also be self-motivated and able to thrive in an international, multidisciplinary team.

The Data Scientist will report to the Predictive Analytics Team Lead under the overall direction of the Lead for the Centre for Humanitarian Data. The incumbent will be expected to work closely with the rest of the Centre team.

Functional responsibilities

The incumbent will be responsible for the following duties but not limited to:

1. Researching partner models to understand their design and potential application in humanitarian operations.
2. Designing new tools and analyses to be used for humanitarian action.
3. Supporting the UN Central Emergency Response Fund in the development of anticipatory action frameworks.
4. Providing technical support to OCHA Country Offices for risk analysis and other technical tasks in support of the humanitarian response plans.
5. Contributing to development of the Centre’s work aimed at ensuring data analytics are used responsibly in the sector.

Education / Experience / Language

Education

• Advanced university degree (Master’s or equivalent), preferably in mathematics, physics, engineering, computer science, statistics, economics or a related discipline is required, OR
• First level university degree (Bachelor’s or equivalent) in combination with two (2) additional years of relevant experience may be accepted in lieu of an advanced university degree.

Work Experience

Required:

• Five (5) years of programming experience in Python/R and their relevant libraries (e.g. Pandas, dplyr).
• Five (5) years of experience in statistical modelling, data analytics, data cleaning and processing.
• An understanding of developer tools such as Git.
• Exceptional communication skills, in order to explain your work to non technical colleagues who may understand the mechanics behind data analysis.
• Experience in understanding partner needs and requirements.

Desirable: (The following experience is optional. Candidates who do not have it are welcome to apply)

• Skills in data visualization and Geographic Information System GIS.
• Knowledge or experience in the humanitarian or development sectors.
• Experience with climate data and climate modelling.

Language

• Fluency in English is required (Both oral and written).
• Knowledge of any of the other UN official languages is an advantage.