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Work for the IMF. Work for the World.

The IMF's Institute for Capacity Development (ICD) seeks dynamic and highly motivated Data & Modeling Analysts (DMAs) with strong skills in data management, research design, and economic analysis.

Successful candidates should have the proven ability to work independently, as well as collaboratively in a team environment. The DMAs will be responsible for a wide range of support including, but not limited to, data management and governance, data/technical implementation, and macroeconomic analysis and modeling, collaboration on software development, and providing support to country economists with the adoption of new software tools.

Supports the structuring, management, and governance of datasets underlying ICD's macroeconomic forecasting models, and the ongoing development and adoption of those modeling frameworks.

• Manage, structure, and maintain the databases and data pipelines underlying the macroframeworks software, ensuring data quality, integrity, and consistent documentation of data lineage.
• Establish and apply data governance standards - including data dictionaries, version control practices, and metadata documentation - in coordination with ICD's broader data management practices.
• Support Fund economists in creating, maintaining, and improving macroeconomic frameworks and models, updating databases and documentation.
• Support country teams with the adoption of the newly developed macroframeworks software, converting databases to a new system, helping with data cleanup and transformations.
• Support country teams in developing and linking macroeconomic models to the macroframework software, transferring models originally developed in Matlab (e.g. Dynare) or in Python environments, using basic programming techniques and internal solution tools.
• Contribute to refinements of the internal software package for macroframeworks and other related tools, by providing feedback, ideas, debugging, and collecting feedback from country desk teams.
• Liaise closely with the IT team on business requirement developments/updates, testing use cases from country teams and developer requests, and contributing to documentation updates.

• Educational development, typically acquired through the completion of a university degree, or equivalent, in data managemet, programming/systems, computer science, statistics, finance, mathematics, economics, or a related field of study, is required.
• Experience and strong interest in macroeconomic modelling and forecasting.
• Relevant work experience in a similar role.
• Excellent data management and analytical skills, including experience with relational databases, data governance, and data quality assurance practices.
• Good knowledge of Python, R, or Matlab, and familiarity with SQL or other database query languages.
• Interest in or experience using large language models (LLMs) for code development.

In addition, the following competencies are critical to the position:

• Strong spoken and written communication in English.
• Sound organizational and data management skills, and ability to handle several responsibilities and work under tight time constraints.
• Ability to work without direct supervision, paying close attention to details and bearing independent responsibility for accuracy.
• Proven experience in dealing with all levels of staff in responding to a wide range of inquiries.
• Ability to use tact, discretion, and sound judgment when dealing with clients and in handling confidential information.

This is a one-year contractual appointment. Contractual appointments at the IMF are renewable for up to four years of cumulative contractual service, pending incumbent's performance, budget availability, and continuous business need.

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The IMF is guided by the principle that the employment, classification, promotion, and assignment of staff shall be made without discrimination against any person. We welcome requests for reasonable accommodations for disabilities during the selection process. Information on how to request accommodations will be provided during the application process.