The University of Groningen (UG), Faculty of Economics and Business, is seeking to appoint a Postdoc researcher / data scientist for a data collection project on securities listed on the Amsterdam Stock Exchange between 1796 and 1980 and their issuers.

Project description
The researcher will be active within “Gauging Past Performance: Creating Financial Metadata for Economics, Finance, and Economic History in The Netherlands”, a project subsidized by Platform Digital Infrastructure Social Sciences and Humanities, 2020-2024 (€ 830,000, Main Applicant: Prof. Herman de Jong, UG).

The aim of this ground breaking project is to build a comprehensive information system holding Dutch corporate and stock exchange data for the period 1796-1980. Historians and economists collaborate closely to provide new and vital data for understanding the long-term evolution of Dutch financial markets, firms and public finance in their societal context. This project supplies innovative standards of documentation, bringing together metadata formats and an architecture facilitating the next generation of data-extraction and enrichment systems from historical sources.

We need this system because comprehensive Dutch data add significantly to current European efforts to provide a necessary corrective to dominant, US-derived, assumptions about modern finance and financial market evolution. The project contributes to the rapidly growing demand for digital corporate information from economists and financial and economic historians. Moreover, the project fits in EURHISFIRM, the H2020 consortium of top universities and institutes developing digitalisation of historical corporate and financial data, awarded by the European Commission.

Tasks:

• Supervise, in collaboration with an experienced research assistant, a team of student-assistants hand-collecting, coding and linking basic reference data for the unique identification of securities and their issuers.
• Check, clean, code and prepare data for import in the database.
• Extract additional data from scans of printed serial sources (e.g. Gidsbij de Prijscourant, Van Oss’Effectenboek, …) and link to securities and issuers present in the database:
o Dividend and interest payments
o Issue sizes (number and amount of securities issued and outstanding)
o Balance sheet and profit-and-loss account information
o Names of directors.
• Assess the feasibility of extracting and linking security prices from the official price list (Prijscourant) of price lists published in newspapers.
• Train and assist PhD students and researchers working with the data in querying the database and processing the data.
• Create an online and publicly accessible interface to browse, search and visualise the data alongside images of source documents.
• Document the data and the data collection, update manuals (e.g. after a database upgrade).

Degree:

PhD in Economics, History, Digital Humanities, or Computer Science

Skills:

• proficiency in relational databases (Oracle SQL in particular)
• programming in Python
• basic understanding of Java
• experience with machine learning, OCR, layout analysis, named-entity recognition.

Fixed-term contract: 27 months.

We offer you in accordance with the Collective Labour Agreement for Dutch Universities:

• a salary depending on qualifications and work experience starting from a minimum of € 3,974 gross per month to a maximum of € 5,439 gross per month (salary scale 11) for a full-time position
• 8% holiday allowance and 8.3% year-end bonus and participation in a pension scheme for employees; favourable tax treatment may apply to non-Dutch applicants
• an appointment for a period of two years and three months, i.e. until 1 January 2025

We expect the candidate to start by October 2022

Faculty of Economics and Business

The University of Groningen is a research university with a global outlook, deeply rooted in Groningen, City of Talent. Quality has had top priority for four hundred years, and with success: the University is currently in or around the top 100 on several influential ranking lists.