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Traineeship in the Stress Test Modelling or Systemic Risk and Financial Institution Divisions

Posted 21 Apr 2026
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Work experience
0 to 1 years
Full-time / part-time
Full-time
Job function
Salary
€1,170 per month
Degree level
Required language
English (Fluent)
Deadline
11 May 2026

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You will be part of either the Stress Test Modelling Division or the Systemic Risk and Financial Institutions Division in the ECB’s Directorate General Macroprudential Policy and Financial Stability.

Our divisions together have around 50 members of staff who identify and assess the main risks to financial stability in the euro area, with a focus on the banking system and its interactions with the wider financial system. We also support microprudential stress-testing activities conducted by the ECB and other European supervisory authorities, covering areas such as credit, market and profitability risks, by providing stress-test scenarios and advanced analytical input. Another area of our work consists of developing state-of-the-art models to assess the implications of climate change for financial stability risks. Additionally, we contribute to systemic risk monitoring, using large granular regulatory and transaction-level datasets together with econometric methods to support evidence-based assessments of financial stability risks and macroprudential policies.

In your role as a trainee in one of these divisions, you will be part of a specialist team carrying out policy-relevant analysis and model development. You will help to develop and maintain the ECB’s stress-testing models, data infrastructure and systems, with a focus on macroprudential stress tests or assessing interconnectedness within the euro area financial system. You will also contribute to the analysis of the interactions between macroprudential policy, financial stability and monetary policy, and their effects on the wider economy.

Your role

As a trainee, you will:

  • provide research support, including data collection and code development, for analytical projects;
  • contribute to official publications on financial stability and macroprudential policy, such as the Financial Stability Review, and support management with internal and external presentations;
  • maintain, update and further develop databases used for stress testing, systemic risk identification and macroprudential policy analysis, as well as databases covering economic and financial indicators;
  • develop visualisation tools and code to improve data processing and user access to complex datasets;
  • work with colleagues across the ECB to maintain and enhance the IT systems used for stress testing.

The traineeship offers you excellent opportunities to expand your knowledge of macroprudential policy and financial stability. From an early stage, you will have opportunities to develop your skills and have a real impact on the work of your division, while learning from experts in the field. You will also be able to attend a wide range of seminars and access the ECB’s library, computing, programming and statistical resources. You will be part of a multicultural team that strives for continuous innovation to make a positive impact on the lives of European citizens.

Qualifications, experience and skills

Essential:

  • a bachelor’s degree or higher in economics, finance, statistics, data science, mathematics, engineering, business administration, computer science, physics or a related field;
  • a sound understanding of, and practical experience with, one or more programming languages or econometric software packages (e.g. Python, R, SQL, MATLAB or Stata);
  • a sound knowledge of statistical and econometric methods, and the ability to present data and results clearly and effectively;
  • experience in data management and in handling and analysing multidimensional datasets;
  • a good knowledge of the MS Office package, particularly Excel;
  • an advanced (C1) command of English and an intermediate (B1) command of at least one other official language of the EU, according to the Common European Framework of Reference for Languages.

Desired:

  • a master’s degree (completed or in the final stages of completion) in economics, finance, statistics, data science, mathematics, engineering, business administration, computer science, physics or a related field;
  • experience with macro- or micro-econometric methodologies;
  • experience with modelling tools (e.g. semi-structural, agent or network-based, dynamic stochastic general equilibrium, mathematical optimisation or simulation models);
  • a sound understanding of financial statement analysis (e.g. bank or financial institution balance sheets) or asset pricing (e.g. derivatives);
  • experience with macroeconomic, financial, banking, corporate or climate-related statistics at the sector or micro-level, including familiarity with commercial databases (e.g. Refinitiv Eikon, Bloomberg, BankFocus or Haver Analytics) or with big data.

You are curious and eager to learn, and want to further develop your ability to analyse complex information. You are keen to collaborate with others, pursue team goals and learn from other people’s diverse perspectives. You strive to know and anticipate stakeholder needs, and will signal any need for change and propose alternative solutions.

You are motivated to contribute to the ECB’s mission, to serve the citizens of the EU as a member of a public institution and to work with colleagues from all over Europe. You are keen to be part of our team and to use your skills and competencies to achieve the aims of this position.

Further information

Initial traineeship of between three and six months, with a possible extension to up to 12 months in total.

Je bent op zoek naar een baan die past bij jouw ambities. Een baan in een internationale omgeving. Werken bij de EU is werken met collega's met een zeer gevarieerde culturele achtergrond. Er zijn carrièremogelijkheden in Brussel, Luxemburg en Straatsburg, maar ook elders in Europa en in de rest van de wereld. De EU biedt volop mogelijkheden voor kandidaten met zeer uiteenlopende opleidingen en ervaring.
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