Evaluation Data Associate
Date: 13 February 2023
Deadline: 06 March 2023 (11:59 PM KST)
Job Category: International
Salary: USD 83,200 net (plus attractive benefits, that include the following allowances (as appliable): Relocation, dependency, education assistance and home country travel)
Contract Duration: 36 months
The mission of the Green Climate Fund (“GCF”, “Fund”) is to assist developing countries to respond to climate change while bringing prosperity to their peoples.
Established in 2010, the GCF invests in transformational climate projects in the developing world. The Fund makes an ambitious contribution to global climate action and channels significant financial resources into developing countries to help build low-emission and climate-resilient societies. It is country-driven and undertakes actions that reflect the circumstances of each country concerned and its national aspirations. The GCF is a key enabler of the 2015 Paris Agreement on Climate Change.
The GCF’s diverse workforce is advancing its mission from its headquarters in South Korea. Our talented staff makes unique contributions to the Fund, enriching the institution through their combined expertise and professional commitment.
The Independent Evaluation Unit (“IEU”) of the GCF is seeking to recruit an Evaluation Data Associate. S/he will be responsible for sustaining the delivery of statistical analysis into evaluations, managing datasets, and aligning quantitative methods to complex research questions. The role requires an excellent grasp of quantitative methods, including data analyses and statistics. For this, s/he will need to also show strong skills in using statistical, visualization and geospatial software packages, such as R, Stata, Excel, Tableau, Power BI, and ArcGIS/QGIS, and have experience in applying such software in evaluation contexts.
Strong statistical skills applied data collection experience, and the ability to apply quantitative methods to complex settings are a must as well as experience in deploying various evaluation methodologies and approaches. As part of a diverse team, s/he will also support the IEU’s desk reviews, report writing, and external relations strategy. The Evaluation Data Associate should have a keen instinct to learn and develop skills they may not have at the onset of the role. The incumbent will be directly reporting to the DataLab Team Lead and/or the Head of the IEU.
Duties and Responsibilities
- Work closely with the team and management to ensure alignment of data analysis with evaluation needs;
- Ensure consistent, high-quality analytical support for evaluations and other outputs of the IEU; ensuring backstopping;
- Conduct qualitative and quantitative data analysis and extraction, ensure the quality of data-related outputs in IEU;
- Use quantitative and geospatial methods to identify trends and patterns in data;
- Execute survey design and facilitate data collection;
- Effectively communicate data and analysis results: both as data visualizations and in writing;
- Ability to spot and troubleshoot data collection, analysis, and reporting problems.
- Identify issues and operational factors which impact the consistent delivery of objectives set in IEU’s work plan; advise on possible remedial approaches to sustain and advance quality;
- Inform process owners on experience-based improvement opportunities for data and evaluation process refinement;
- Engage with consultants, experts, and stakeholder groups for surveys both on- and offline, (phone) interviews, and other types of data collection;
- Undertake basic tasks such as data extraction, general evaluation support and also work with consultants and interns for this purpose as well as to do sophisticated analyses;
- Deliver background support to IEU’s external consultant projects, including initial screening and review of project/programme funding proposals and concept notes, interactions with accredited entities in bilateral meetings, preparation of assessment findings, maintenance of the operations database;
- Support any additional analytical and operational tasks as assigned by the IEU; and
- Perform other related duties, as required.
- Deliver high-quality analysis, spatial analysis and perform quality assurance for evaluations and other output products of the IEU in the field and at headquarters;
- Provide organizational and substantive support for GCF Board meetings and other events and meetings related to the functioning of the IEU, for example, assisting in the preparation of relevant documentation, taking meeting minutes, preparing summaries of discussions, meeting reports, drafting agreements and other legal documentation; and
- Ensure lessons learned from ongoing and past evaluations are identified and implemented.
Requirements (Education, experience, technical competencies required of the job)
- Master's Degree in statistics, applied statistics, mathematics, economics, finance, econometrics, climate sciences or related fields.
- At least two years of relevant work experience in a professional capacity, such as experience in the climate change, development and economic sector, within an international organization, development agency, governmental, private sector or non-profit sector;
- Proven track record in data collection, analysis, and statistical skills for assessment and evaluation work. Full proficiency in applying technical skills in complex settings beyond your formal training;
- Proven track record in development and environmental projects, including field experience and experience with larger panel datasets;
- Ability to articulate complex issues verbally and in writing in a concise manner;
- Mature judgment and absolute commitment to confidentiality;
- Familiarity with climate change topics, public health, and international politics is desirable;
- Any UN language will be an advantage, particularly Spanish would be considered an asset.
The closing date for application is 06 March 2023. Applications submitted after the deadline may not be considered.
*The person assessed by the Selection Panel as most suitable for the position will be proposed for appointment. Selection among short-listed candidates will also take into account performance at interview, appropriate testing, and references.
Applications from women and nationals of developing countries are strongly encouraged.