Humanitarian Operations Senior Officer (Data Analysis and Anticipatory Action)

UNOPS supports partners to build a better future by providing services that increase the efficiency, effectiveness and sustainability of peace building, humanitarian, and development projects.  Mandated as a central resource of the United Nations, UNOPS provides sustainable project management, procurement, and infrastructure services to a wide range of governments, donors, and United Nations organizations. The New York Portfolios Office (NYPO) supports the United Nations Secretariat, as well as other New York-based United Nations organizations, bilateral and multilateral partners, in the delivery of the UNOPS mandate in project management, infrastructure management, and procurement management.

The Sustainable Development Cluster supports diverse partners with their peacebuilding, humanitarian, and development operations. It was formed by combining the following portfolios: Grants Management Services, UN Technology Support Services (UNTSS), and the Development and Special Initiatives Portfolio.  It provides services to partners' programmes that are designed, structured, and managed with a global perspective and primarily serving partners that are headquartered in New York.  SDC has a footprint of approximately 125 countries.

UNOPS has signed an agreement with the United Nations to implement defined activities in support of the United Nations Office for the Coordination of Humanitarian Affairs (OCHA).

The Central Emergency Response Fund (CERF) is a global humanitarian fund with a long-time funding target of $1 billion annually. It is one of the fastest and most effective ways to support rapid humanitarian response for people affected by natural disasters and armed conflict. CERF receives voluntary contributions year-round to provide immediate funding for life-saving humanitarian action anywhere in the world.

CERF continuously strives to improve the quality of decisions on funding allocations, with two main objectives: First, to make allocations as early as possible, sometimes before a shock happens or before the peak humanitarian impact materializes. Second, to make allocation decisions based on systematic evidence and rigorous analysis. This requires data collection, monitoring and analysis to inform decision-making. 

A rigorous data analysis in particular underpins CERF’s work on anticipatory action, as well as the process for selecting countries for twice-yearly allocation rounds to underfunded emergencies.

Purpose and Scope of Assignment 

The project is seeking to expand its team with a Humanitarian Operations Senior Officer (Data Analysis and Anticipatory Action), to support its work to improve data analysis and to support the anticipatory action portfolio. The incumbent will contribute dedicated data analysis expertise and knowledge and coordinate and guide data analysis within CERF. The incumbent needs to be self-motivated and be able thrive in an international, multidisciplinary team. The right candidate has the skills to work independently and with a team to provide guidance on data-related processes to a diverse audience, takes initiative where needed and demonstrates problem-solving skills. 

The incumbent of this position will be personnel of UNOPS under its full responsibility.

The functional responsibilities include:

• Support the development of new anticipatory action frameworks or contribute data analysis, specific expertise and dedicated knowledge to the development of new frameworks, the revision and improvement of existing frameworks, ensuring that frameworks align with CERF’s criteria and objectives and that triggers are based on rigorous data analysis.

• Guide AA teams across headquarters and country operations and facilitate the development of key components of collective AA frameworks (action plan, crisis timeline, trigger mechanism based on predictive data analytics, etc.) and provide expertise through research, data analysis, presentation and facilitation. 

• Monitor specific AA frameworks, including whether trigger conditions have been met based on data analysis, and facilitates the activation of AA frameworks when agreed triggers have been reached, including the development or review of CERF applications (projects and budgets), ensuring that activities are anticipatory in nature and in line with CERF’s life-saving criteria, and ensuring that projects can be approved immediately and money disbursed quickly

• Inform the work on anticipatory action frameworks by providing data analysis, advising on CERF processes and criteria, drafting frameworks, potentially participating in missions to countries to set up or revise frameworks and in other ways required.

• Conduct the data analysis underpinning the 2024 first allocation round for underfunded emergencies. This includes collecting data, monitoring data trends, calculating the CERF Index for Risk and Vulnerability (CIRV – a composite index), analysing and visualizing data and interpreting the results so that they can inform decision-making.

• Conduct data analysis informing other potential CERF allocations, including multi-country allocations (similar to the multi-country allocations in response to the arrival of refugees and others fleeing the conflict in Sudan), special allocations (similar to the food security and famine prevention allocations of 2022 and 2023), early action (e.g., in response to the current El Niño episode) and regular rapid response allocations (e.g., estimating the number of people affected by a tropical cyclone before assessment data is available).

• Analyse data collected via the CERF’s standard indicators, interpret the data to identify key trends and results and present these so that they can inform CERF’s annual report, presentations to CERF’s Advisory Group and can be used for other advocacy or fundraising purposes.

• Review CERF funding requests, advise the Emergency Relief Coordinator – based on a thorough analysis, whether CERF should provide funding or not and how much. Review strategies and project proposals to ensure their quality, and process these in CERF’s grant management system. Review and process project revision requests, interim updates and final reports.

• Contribute to the preparation of various written documents, e.g., drafts sections of reports, background papers, policy guidelines, presentations on anticipatory action, etc. 

• Maintain awareness of current humanitarian affairs and related issues, to include relevant political, policy, gender considerations or other developments in specific subject area, country or region concerned.

• Perform other duties as may be reasonably required and in line with the incumbent’s scope of services above.

Work implies frequent collaboration with the following: 

• Personnel at all levels within OCHA/UNOPS in New York, Geneva, country and regional offices as needed

• Counterparts in other UN agencies, NGOs and research institutions

• Work potentially includes travel to countries with humanitarian contexts or for surge support, workshops, seminars, trainings, etc.

• Advanced university degree (Master's degree or equivalent) preferably in Data Science, Geosciences, Informatics, or a related field is required.

• A first-level university degree (Bachelor's degree or equivalent) in combination with two additional years of relevant experience may be accepted in lieu of the advanced university degree.

Required:

• At least two (2) years of experience with pooled fund-related data management and/or data analysis is required. 

• Direct experience and understanding of humanitarian pooled funds and anticipatory humanitarian action are required, whether with the UN or an NGO.

Desirable: (The following experiences are optional. Candidates who do not have them are welcome to apply)

• Excellent interpersonal skills, ability to solve problems and work independently.

• Ability to analyze and integrate diverse and complex quantitative and qualitative data from various sources.

• Ability to interpret complex data sets and identify key trends and other factors to inform decision-making.

• Database management and data analysis skills.

• Experience with conducting data analysis in Python or similar programming language and experience with applied geospatial data science using ArcGIS or similar software.

• Fluency in English (read, write, speak) is required.

• Please note that UNOPS does not accept unsolicited resumes.

• Applications received after the closing date will not be considered.

• Please note that only shortlisted candidates will be contacted and advance to the next stage of the selection process, which involves various assessments.

• UNOPS embraces diversity and is committed to equal employment opportunity. Our workforce consists of many diverse nationalities, cultures,  languages, races, gender identities, sexual orientations, and abilities. UNOPS seeks to sustain and strengthen this diversity to ensure equal opportunities as well as an inclusive working environment for its entire workforce. 

• Qualified women and candidates from groups which are underrepresented in the UNOPS workforce are encouraged to apply. These include in particular candidates from racialized and/or indigenous groups, members of minority gender identities and sexual orientations, and people with disabilities.

• We would like to ensure all candidates perform at their best during the assessment process.  If you are shortlisted and require additional assistance to complete any assessment, including reasonable accommodation, please inform our human resources team when you receive an invitation.

Terms and Conditions 

• All UNOPS personnel are responsible for performing their duties in accordance with the UN Charter and UNOPS Policies and Instructions, as well as other relevant accountability frameworks. In addition, all personnel must demonstrate an understanding of the Sustainable Development Goals (SDGs) in a manner consistent with UN core values and the UN Common Agenda.

• It is the policy of UNOPS to conduct background checks on all potential personnel. Recruitment in UNOPS is contingent on the results of such checks.