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Research Analyst / Senior Research Analyst - SPRRU

Imf

·

Jun 12, 2026

Location
IMF Headquarters 1, United States
Type
Full-time
Department
Education
Seniority
Senior
Closing date
Jun 26, 2026
Source
Workday

Description

Work for the IMF. Work for the World.

 

The Strategy, Policy, and Review Department’s (SPR) Macro-Risk Unit works on assessing global and domestic risks across a range of economic sectors for all countries in the membership. The group is fast-paced, innovative, and technology-focused. Research assistants (RAs) provide critical  support to the unit, ingesting and managing data, developing and interpreting cutting edge analytical tools for risk assessment, and creating and maintaining a suite data visualization tools to communicate complex machine-learning model output and other analytical work internally and externally. The successful candidate will be the lead of other RAs in the unit and coordinate work across dedicated and part-time RAs.

Main Responsibilities:

  • Design, build, document, and maintain systems to ingest and transform external and in-house data series with careful attention to source definitions, transformations, and vintages.

  • Import, process, consolidate, and transform data sets within and between databases using statistical and/or econometric techniques, typically requiring programming.

  • Analyze economic, financial, or statistical relationships in databases, identifying key relevant data series and novel datasets.

  • Use of text analysis and natural language processing techniques to retrieve relevant information from documents.

  • Develop and maintain innovative data visualization tools to communicate complex nonlinear model results to economists.

  • Participate in the design and estimation of innovative risk assessment models to track emergent global and country-specific risks.

  • Prepare Power Point presentations collecting the work of the unit.

  • In addition to the above, the selected candidate may carry out other assignments as instructed by the Unit Chief or Deputy Unit Chief.

The successful candidate will have the following:

  • Educational development, typically acquired by the completion of a university degree, or equivalent, in economics, finance, statistics, computer science, or a related field of study is required.

  • Proficiency in Excel and strong Word and PowerPoint skills are a necessity.

  • Strong programming skills in Python, R, Stata, and MATLAB.

  • Expertise in empirical forecasting, especially with tree-based and boosted models, ideally with experience in Machine Learning time series panel estimation, model design, and evaluation.

  • Knowledge of macroeconomic theory and concepts is required, with experience in macroeconomic and financial crises a plus.

  • Strong knowledge of data visualization tools, especially PowerBI.

  • Any experience contributing to academic or policy-oriented economic research is a plus.

  • Innovation, creativity, strong communication skills, and drive for results. 

  • Ability to lead a team of dedicated and part-time RAs through complex, multi-stage processes and prioritize key work processes and objectives.

Only candidates who are currently residing in the Washington DC metro area will be considered.

This vacancy shall be filled by a 3-year Term appointment in accordance with the Fund’s employment rules. This term position, while extendable for up to 3 years, is not viable for conversion to open-ended staff.

All applicants are expected to include a Statement of Interest as an attachment to the application, which may be used in the screening process for this vacancy.

Department:

SPRAI RU Strategy, Policy, and Review Dept. Immediate Office Macro Risk Unit

Hiring For:

A06, A07, A08

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.

Skills

PythonMATLABMachine LearningExcelR

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