Student Assistant in Macroeconomic Forecasting and Data Science

We are looking for individuals with a strong interest in applied macroeconomics, economic forecasting, data science, and empirical research. The main task will be to support the collection, cleaning, harmonization, and documentation of macroeconomic data. Depending on skills and interests, the position may also involve contributing to the construction of the reanalysis dataset, reproducible data pipelines, descriptive analysis, and forecasting-related tasks.

Prior experience in handling and analysing data using statistical software packages such as R, Python, and/or Matlab is desired. A strong interest and drive in developing these skills is expected.

Your tasks may include:

• Collecting macroeconomic data from public statistical offices, central banks, international organizations, and data providers such as Macrobond
• Research on the availability of real-time data vintages, release calendars, publication lags, variable definitions, and data revisions
• Cleaning, harmonizing, transforming, and documenting macroeconomic time series across countries, sectors, regions, and frequencies
• Supporting the creation of a reproducible macroeconomic reanalysis dataset, including metadata, transformation codes, and versioning routines
• Building and maintaining data acquisition routines, including APIs, web scraping, and automated downloads where feasible
• Conducting descriptive analysis and consistency checks of macroeconomic indicators
• Supporting the preparation of datasets for forecasting models, including dynamic factor models, BVARs, and machine-learning-based approaches.

You must be enrolled at a Swiss University and willing to work between 1 to 2 days per week (15h). At KOF, working time is typically handled very flexibly such that you can take time to study for exams or fulfill other obligations for your studies while coordinating with the research staff at KOF when tasks need to be completed.