The International Monetary Fund seeks a dynamic and highly motivated Research Analyst (RA) with strong quantitative and analytical skills. The successful candidate should have the proven ability to work independently, as well as collaboratively in a team environment. The Research Analyst will be responsible for a wide range of support including, but not limited to, data gathering, analysis of economic or statistical data sets, programming for model development and high-quality analyses, and model execution. This is a contractual appointment for one year, renewable for up to four years of cumulative contractual service, depending on the business need and performance of the incumbent.

Research analyst positions are filled with candidates physically residing in the local Metropolitan Washington, D.C. area.

Description

The candidate will be assigned to work in the Economic Modeling Division in the Research Department of the IMF. The division focuses on two major workstreams, both of which support bilateral and multilateral surveillance: (i) to apply and further develop the division’s suite of large global macroeconomic models, and (ii) to monitor high frequency global macroeconomic data and produce a top-down global quarterly forecast.

The candidate will support the first workstream. The work with the division’s large global models focuses on the development and application of the central work horse models maintained in the division. The range of issues that confront multilateral and bilateral surveillance is constantly expanding and the division’s models need to constantly be extended to address these issues. Current development work is focused on quantifying the impact on the macroeconomy of policies aimed at reducing carbon dioxide emissions.

Major Duties and Responsibilities

Support division objectives on economic analysis, managing information technology & systems, and model development. Analyzes and computes statistical and economic data in support of the division.

• Compile statistical data, compare and evaluate alternative data sources, and ensures consistency of series and definitions.
• Compute data collected using statistical and econometric techniques and develop summary analysis, including summary tables and charts for various projects.
• Maintain relevant computer software, and writes, updates, modifies, and executes computer programs for statistical and model-based analysis.
• Participate in divisional/departmental research projects.

Minimum Qualifications

Bachelor’s degree in Economics, Finance, Statistics, Mathematics, Computer Science, Data Science or other related quantitative field, but more competitive candidates would have a Master’s degree in Economics with coursework or a demonstrated aptitude in Computer Science.

Two years of relevant work experience in a similar role:

• Proficiency in the use of analytical, statistical and econometric software packages such as MatLab, Dynare, Python, and R.
• Proficiency in MS Excel, including basic functions and formulas.

Preferred:

• Some grounding in macroeconomic theory (monetary and fiscal). Knowledge of climate change issues a plus, but not required.
• Experience working with macroeconomic data.
• Experience in computer programming such as Python and R. Knowledge of MatLab and Dynare a plus.
• Experience and ability to use visual presentation tools such as PowerPoint, MS Excel charts or other similar tools.
• Knowledge of TROLL and FAME would be a plus, but not required.

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

• Proven ability to manage large and complex databases and develop summary analysis, including summary tables and charts, and sound analytical and problem-solving skills including a knowledge of statistical applications and techniques.
• 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 detail and bearing independent responsibility for assigned tasks.
• Ability to use tact, discretion, and sound judgment when handling confidential information.