Specific duties and responsibilities include but are not limited to:

• Contribute to data-focused analytical work on gender and inclusion-related topics, including financial inclusion.
• Work on expanding the coverage and analytical content of the Gender Data Hub, in support of the IMF’s Strategy Toward Mainstreaming Gender.
• Support the internal training program including by designing and delivering sessions on gender-related data issues to IMF staff.
• Contribute to review of gender and inclusion related relevant policy and country documents and data related issues.
• Manage the production and dissemination of gender statistics part of the Gender Data Hub and related databases, with metadata and methodology documentation and updates.
• Support the modernization and continuous improvement of the Gender Data Hub and management and processes for producing, curating, and disseminating gender and inclusion related data and statistics.
• Provide support to country teams on queries related to gender data and on troubleshooting issues with the Gender Data Hub.

Requirements:

• An advanced degree in Economics, Statistics and/or related field, supplemented by a minimum of four years of relevant professional experience is required.
• A strong data science, statistics, quantitative and computational background.
• Experience in working on gender and inclusion related issues, disaggregated data, and data management would be an asset.
• Strong organizational and time-management skills to be able to manage complex tasks with many stakeholders under tight deadlines.
• Strong analytical skills and technical experience in various aspects of the data management pipeline; data acquisition, cleaning and management; curation; interpretation and analysis; and presentation.
• Strong understanding of data and metadata management and how it can be aligned with users’ needs for better discovery and retrieval of data.
• Knowledge of current and emerging technologies around data management systems and tools would be an asset.
• Knowledge of one or more mainstream programming language for data analytics (R, Python, Java, etc.) would also be an asset.
• Excellent written and verbal communications skills. In particular, the candidate will exhibit the ability to communicate ideas effectively and to interpret statistical data quickly and clearly, including with informative graphs and charts.
• Strong interpersonal skills and experience in working in a multicultural team environment with multiple priorities.