The KOF Swiss Economic Institute at ETH Zurich is the leading institute for applied research in economics in Switzerland.

KOF has a strong collaborative environment that promotes exchange between research and administrative staff across different levels and functions and is committed to rigorous, applied research on policy-relevant topics with a connection to Switzerland.

For the KOF Research Division Macroeconomic Forecasting and Data Science, we are seeking a student assistant to support a research project on macroeconomic reanalysis data and machine-learning-based economic forecasting. The position is available as soon as possible for an initial duration of six months.

The project aims to build a harmonized macroeconomic reanalysis dataset that combines international, national, and sub-national macroeconomic indicators, preserves real-time data vintages, documents publication lags and revisions, and creates a reproducible data backbone for modern forecasting methods.

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.

A job that makes a difference: Join ETH Zurich, which not only supports your professional development but also actively contributes to positive change in society. You can look forward to numerous benefits, a wide range of sports activities organised by the ASVZ, childcare 

• health benefits: discounts on health-related services and access to
• a flexible working environment: opportunities for flexible working hours and a supportive learning environment.
• Professional development: Support for training and further education initiatives to enhance employability.

These benefits are designed to promote both personal and professional development whilst working at ETH Zurich.

We look forward to receiving your online application until 24 July 2026 with the following documents:

• Cover letter (short)
• Curriculum vitae
• Transcript of records of studies up to date or graduation records

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about KOF Swiss Economic Institute can be found on our website. Questions regarding the position (no applications) should be directed to KOF HR ([email protected]).