Student Research Assistant Traineeship Programme – Monetary Policy Research/Senior Management/Research Task Force on Artificial Intelligence

Your role As a Student Research Assistant Trainee you will:work with datasets, including macroeconomic data and granular firm-, bank- and household-level data;work with macroeconomic models, including developing and solving New-Keynesian models, HANK models and models with financial frictions; work with macro-econometric models, including developing and estimating structural vector autoregression models and non-linear time-series models;work closely with the Division’s economists and research analysts, supporting the team in daily tasks and analytical projects;contribute to the Division’s research-based policy advice by using data analysis and econometric and macroeconomic modelling tools to help with empirical and quantitative assessments.The traineeship offers you excellent opportunities to enhance your quantitative skills and work with experienced economists while gaining insight into analysis and policy within a central bank. It will expose you to ideas, debates and challenges that will provide a useful foundation for your future career and/or postgraduate studies. You will have access to internal seminars and conferences organised by the ECB. 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, statistics, finance, data science, mathematics, engineering or a related field; practical knowledge of one or more of the following programming languages: Python, R, Stata or MATLAB;knowledge of econometrics (time series econometrics, econometrics of panel data and micro-econometrics), statistics and data science (web scraping, text analysis and other advanced machine learning techniques), and model solution methods (e.g. perturbation methods and global methods);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 .Desired: a master’s degree or completion of at least one year of study towards obtaining a PhD degree in economics, statistics, finance, computer science, mathematics, engineering or a related field;experience in at least one of the following areas: econometrics (e.g. time series econometrics, econometrics of panel data and micro-econometrics), statistics and data science (e.g. web scraping, text analysis and other advanced machine learning techniques), and model solution methods (e.g. perturbation methods and global methods);experience with web-based tools for the LaTeX typesetting system (e.g. overleaf);experience of cloud computing (e.g. Amazon AWS);experience with supporting research, such as providing data support for research projects or papers;experience with one or more of the following: macroeconomic data, firm-level data, accounting data, supervisory banking data, financial market data, other microdata, survey data analysis (e.g. using national surveys, the Eurosystem’s Household Finance and Consumption Survey, the EU Labour Force Survey or others) or large datasets;experience using market data services, such as Bloomberg, LSEG Workspace (previously Refinitiv Eikon and/or Datastream), Haver Analytics, SNL Financial, Moody’s Analytics BankFocus (formerly Bureau van Dijk’s Orbis BankFocus) and Moody’s Orbis Europe.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.