Key Background & ExperienceMaster’s degree or PhD, in data science, finance, statistics, economics, mathematics, physics, or other closely relevant field.
At least two years of relevant work experience are required. For PhD holders, up to two years of relevant research work performed in the context of PhD studies can be considered as relevant work experience.
Experience in quantitative analysis applied to macroeconomic, financial market or other large-scale economic and financial datasets.
Familiarity with a broad range of commonly used databases and data providers for macroeconomic and financial data (e.g. Datastream, Bloomberg, Haver Analytics, Dealogic, SNL, etc.) and official financial sector statistics (e.g. those produced by the European Central Bank, Eurostat and the Bank for International Settlements).
Experience with relational databases (e.g. PostgreSQL) and data modelling.
Experience with data visualisation and business intelligence tools (e.g. Power BI).
Good knowledge of macroeconomics, including quantitative/econometric skills.
Proven programming skills in Python. Experience with Matlab and other statistical packages is an advantage.
Experience with machine learning and other advanced analytical techniques would be an asset.
Familiarity with modern software development practices, including Git-based workflows, automated testing, CI/CD pipelines (e.g. Jenkins), and collaborative software development.
Experience working with APIs, data integration workflows, or analytical data platforms would be an advantage.
Some experience in international and European financial institutions is a plus.
Excellent oral and written English skills.
Key CompetenciesAnalytical and problem-solving skills
Contract duration: Four years, with possibility of extension
Place of employment: Luxembourg
Current working arrangements: possibility to work remotely, normally up to two days a week, from Luxembourg and the border region (or from further away under certain conditions).
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