Tenure-Track Faculty Position in Business Analytics – Hanken School of Economics
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Tenure-Track Faculty Position in Business Analytics – Hanken School of Economics
Hanken School of Economics invites applications for a tenure-track faculty position in Business Analytics at the level of Assistant Professor, Associate Professor, or Full Professor. The position is based in Helsinki within the subject of Statistics, part of the Department of Finance and Economics.
Position Overview
Particulars | Details |
|---|---|
Institution | Hanken School of Economics |
Position | Assistant Professor / Associate Professor / Full Professor |
Field | Business Analytics |
Subject | Statistics |
Department | Department of Finance and Economics |
Appointment Type | Tenure-Track |
Location | Helsinki, Finland |
Expected Start Date | 1 January 2027, or as otherwise agreed |
Latest Start Date | 1 September 2027 |
Application Deadline | Not specified in the provided excerpt |
About the Opportunity
The position forms part of Hanken School of Economics' tenure-track system and is open to researchers with the potential for an outstanding academic career.
Candidates appointed at the Assistant Professor or Associate Professor level will have the opportunity to advance through evaluations conducted in accordance with Hanken's tenure-track guidelines.
The Statistics unit collaborates closely with Finance and Information Systems and conducts research including work on financial time series. The position is intended to strengthen research and teaching in the application of machine learning and business analytics.
Teaching is provided at the Bachelor's, Master's, and doctoral levels.
Research Areas
The position is particularly relevant to quantitative research areas such as:
Business Analytics
Data Science
Machine Learning
Management Science
Statistics
Econometrics
Quantitative Economics
Applied Mathematics
The department emphasizes high-quality research relevant to business and economics, including publication in highly ranked academic journals.
Requirements
Applicants will be evaluated based on their:
Research
Teaching
Institutional service
Societal impact
For the current position, applicants are required to have a fluent command of both English and Swedish.
Teaching in Swedish is expected as part of the responsibilities of the position.
Assistant Professor Requirements
Applicants at the Assistant Professor level should:
Hold a doctoral degree, or be near completion of their doctorate
Have a strong quantitative research orientation
Demonstrate potential to conduct high-quality scientific research in areas relevant to Business Analytics
Demonstrate potential to provide high-quality teaching
Relevant doctoral/research backgrounds may include Business Analytics, Data Science, Machine Learning, Management Science, Statistics, Econometrics, Quantitative Economics, or Applied Mathematics.
Associate Professor & Full Professor Requirements
The provided excerpt confirms that candidates may apply at the Associate Professor or Full Professor level.
However, the specific qualification and experience requirements for these levels are not included in the provided excerpt and should be checked in the complete official vacancy announcement.
Teaching & Research Environment
The successful candidate will join a research-oriented business school offering education in Swedish and English.
The Statistics subject seeks to strengthen its teaching and research activities in machine learning and business analytics, while maintaining close collaboration with related areas such as Finance and Information Systems.
Salary & Benefits
Not specified in the provided excerpt.
Important Dates
Expected Start: 1 January 2027, or as otherwise agreed
Latest Start: 1 September 2027
How to Apply
Application instructions and the direct application link are not visible in the provided excerpt. Candidates should refer to the complete Hanken School of Economics vacancy announcement for application procedures, required documents, and the closing date.
Job Domain: Business and Economics – Business Analytics / Statistics / Data Science / Machine Learning
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