Expert in Financial Sector Assessment and Policies

Job Posting Organization:
The International Monetary Fund (IMF) is a global organization established to promote international monetary cooperation, facilitate balanced growth of international trade, and provide resources to member countries in need. Founded in 1944, the IMF has grown to include 190 member countries, each contributing to the fund's financial resources. The organization employs over 2,700 staff members from diverse backgrounds and operates in various countries around the world, focusing on economic stability and financial integrity.

Job Overview:
The position is within the Monetary and Capital Markets Department (MCM) of the IMF, specifically in the Financial Sector Assessment and Policies (FS) Division. The role requires an experienced expert with exceptional skills in risk analysis, stress testing, and financial stability/systemic risk analytics. The selected candidate will be responsible for managing and reviewing the Financial Sector Assessment Program (FSAP), developing policies and instruments, and applying analytical tools for financial stability assessment. The expert will also engage in disseminating these tools through technical assistance and teaching, contributing to the Division's analytical agenda, and collaborating with specialists both within and outside the Fund.

Duties and Responsibilities:
The expert will take on several key responsibilities, including: managing and reviewing the FSAP, developing and applying stress testing and systemic risk assessment tools, and contributing to the Division's regular review work. The candidate will also support Division-wide projects, such as producing board papers, and will be expected to actively participate in FSAP missions as a stress tester or mission leader. This role involves analyzing emerging risks, particularly from Non-Bank Financial Institutions (NBFIs) and market finance, and strengthening system-wide risk analysis. The expert will work closely with senior staff and country authorities, and will be involved in technical assistance and teaching related to quantitative risk assessment.

Required Qualifications:
Candidates must possess an advanced university degree, preferably a Ph.D., in economics, finance, or a related field. A minimum of four years of relevant experience is required. The ideal candidate should be motivated, innovative, and familiar with technical work on assessing financial stability. Proficiency in econometric modeling, including panel regressions and structural vector autoregressions, is essential. Additionally, the ability to code in quantitative modeling software such as MATLAB, R, Python, and Stata, as well as familiarity with advanced AI tools for risk analysis, is desirable. Strong oral and written communication skills are also necessary, along with the ability to work effectively under tight deadlines.

Educational Background:
An advanced university degree in economics, finance, or a related field is required for this position. A Ph.D. is preferred, indicating a high level of expertise and understanding of complex financial systems and economic theories.

Experience:
Candidates should have at least four years of relevant experience in the field of financial stability analysis, risk assessment, or related areas. This experience should demonstrate a strong understanding of the financial sector and the ability to apply analytical tools effectively.

Languages:
While the job description does not specify mandatory languages, proficiency in English is likely essential given the international nature of the IMF and the requirement for strong communication skills. Additional languages may be beneficial but are not explicitly stated as necessary.

Additional Notes:
This position is a two-year contractual appointment, with the possibility of renewal for up to four years of cumulative contractual service, contingent upon performance, budget availability, and ongoing business needs. The IMF promotes a non-discriminatory hiring process and welcomes requests for reasonable accommodations for disabilities during the selection process.