Your role

As a trainee in the Forecasting and Policy Modelling Division you will:

develop and maintain structural, semi-structural and time-series models for the euro area and its member countries;

programme and maintain mathematical, statistical and econometric procedures needed for policy input and research projects;

contribute to ECB and Eurosystem macroeconomic projections, for example by supporting and automating the production and presentation of model-based forecast interpretations and risk scenarios;

construct and maintain monetary, financial and economic databases that contribute to research projects relating to forecasting, macroeconomic modelling and policy analysis.

The position offers you excellent opportunities to work closely with an experienced and highly motivated team of economists and managers, typically in analytics, research support or model development. These traineeships are aimed at students or recent graduates with strong quantitative skills and an interest in policy-related applied research. You will have the chance to develop your analytical skills and gain insights into the ECB’s research activities and policymaking processes, as well as gaining exposure to new ideas and stimuli that will benefit your future career. 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: 

for a traineeship paid at €2,120: a master’s degree and at least two years of PhD studies in economics, statistics, finance, computer science, mathematics or a related field;

for a traineeship paid at €1,170: a bachelor’s degree or higher in economics, statistics, finance, computer science, mathematics or a related field;

in addition to the above, familiarity with macroeconomic and financial statistics contained in international databases, such as the ECB Statistical Data Warehouse and IMF International Financial Statistics, or databases maintained by Eurostat, the OECD or Bloomberg;

a very sound knowledge of spreadsheet and visualisation tools, such as MS Excel, MS PowerPoint, R or Python libraries;

strong programming skills, preferably in MATLAB, Python or R;

experience in the area of macroeconomic modelling, in particular with one or more of the following methods: semi-structural, DSGE, sequence space Jacobian, Bayesian vector autoregression (VAR), factor, structural identification and/or non-linear filtering in time series models; text analysis, neural networks, random forests, other machine learning methods or other macroeconomic models; and the use of related software (e.g. MATLAB toolboxes, TensorFlow/PyTorch or Dynare);

a sound knowledge of the MS Office package;

an advanced (C1) command of English and an intermediate (B1) command of at least one other official language of the EU, according to the .

Desired: 

for a traineeship paid at €1,170: at least one year of completed master’s studies in economics, statistics, finance, computer science, mathematics or a related field;

a sound understanding of macro- and monetary economics;

knowledge of version control software (e.g. Git) or database development languages (e.g. SQL);

a completed project (e.g. thesis, dissertation or research paper) demonstrating advanced quantitative modelling skills, e.g. using DSGE models or Bayesian techniques or non-standard data sources, e.g. from the Web, newspaper articles, etc.

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.