26/10/2026

European Central Bank, Traineeship in the Monetary Analysis Division in the Directorate General Monetary Policy

Attività

Work with datasets, including macroeconomic and microeconomic data and high-frequency financial data;
maintain, develop and enhance the Division’s data infrastructure, including its management tools and dashboards;
work closely with the Division’s economists and research analysts, supporting the team with daily tasks and analytical projects;
contribute to the Division’s input into monetary policy decision-making by using data analysis and statistical and econometric tools to help with empirical assessments;
update charts and tables for regular internal and external reports and presentations, liaising with other ECB business areas.

Essential:

a bachelor’s degree or higher in economics, finance, econometrics, mathematics, statistics, data science, social sciences, computer science or another related field;
experience with statistical and econometric software, such as Python, R, Stata and/or MATLAB;
experience with one or more of the following types of economic data – macroeconomic data, financial market data, firm-level data, accounting/supervisory bank data, transaction-level data, high-frequency data, panel data, survey data, other microdata or large datasets (i.e. big data);
an understanding of the economic issues covered by the Division;
a good knowledge of the MS Office package, especially Excel and PowerPoint;
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 in economics, finance, econometrics, mathematics, statistics, data science, social sciences, computer science or another related field (or being close to completing a master’s degree in one of these fields);
experience working with relational databases, using SQL or other big data analytic tools;
experience using visualisation tools, such as Shiny or Plotly/Dash;
experience in econometrics (especially time series econometrics, econometrics of panel data and microeconometrics), or statistics and data science (e.g. web scraping, text analysis or other advanced machine learning techniques);
experience with assisting research, such as providing data support for research projects;
experience using market data services, such as Bloomberg, LSEG (Workspace and/or Datastream), iBoxx, Haver Analytics, S&P Global Market Intelligence, Moody’s Analytics BankFocus and Orbis Europe.