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  3. PhD candidate in Marketing Analytics for Multi-Touchpoint Customer Journeys and Attribution

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PhD candidate in Marketing Analytics for Multi-Touchpoint Customer Journeys and Attribution

The Amsterdam Business School (ABS) has a vacancy for a PhD candidate in Marketing Analytics for Multi-Touchpoint Customer Journeys and Attribution.
This project is on the management of multi-touchpoint customer journeys and attribution models, with ...

11 maanden geleden


Amsterdam, Noord-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
38 uur
€ 2222 - € 2840 per maand


The Amsterdam Business School (ABS) has a vacancy for a PhD candidate in Marketing Analytics for Multi-Touchpoint Customer Journeys and Attribution.

This project is on the management of multi-touchpoint customer journeys and attribution models, with additional focus on pricing, profit/revenue consequences and resource allocation problems. The candidate is expected to use econometric methods, modelling techniques and different data science approaches/methods in this project. The new PhD candidate is expected to strengthen the Marketing Group at ISM Department within Amsterdam Business School. Candidates must be willing and able to conduct research consistent with the high standards of the ABS, have strong analytical and problem solving skills and background/knowledge in statistics and modelling. The research produced by the candidate will be part of a larger project on customer journeys. The candidate will be working with datasets of an industry partner that entail information on consumer behaviour over a prolonged period of time. The candidate will be involved in linking theory and practice together, particularly in the field of customer journey and customer loyalty. We are looking for ambitious high-potential candidates who are demonstrably committed to excellence in high-impact research, and therefore devout to publish, in top-tier international journals.

This research is part of the collaboration between Amsterdam Data Science and VIVAT Insurance (Zwitserleven & Reaal).


  • A Master’s degree in the area of business, econometrics, economics, data science, or a related discipline such as: engineering, computer science, or applied mathematics;
  • excellent grades and a strong interest in quantitative research methods, modeling and/or statistics;
  • considerable knowledge/experience and willingness to work with R, MATLAB, or Python (one of these environments);
  • the drive to publish in top academic journals in management and business science;
  • well-developed analytical skills, strong organization and communication skills, an entrepreneurial mind set, and perseverance;
  • the ability to work independently in developing the research project;
  • mastery of both written and spoken English;

In addition to these formal requirements, candidates are selected on the basis of their CVs, academic references, grade overviews, and interview(s) with the potential supervisor(s). Research experience on touchpoint attribution is preferred but not required.

Candidates outside of Marketing are encouraged to apply.


The appointment will be for a period of 4 years, with an intermediate evaluation after 18 months, resulting in a PhD thesis. An educational plan will be drafted that includes attendance of courses and (international) conferences. The PhD candidate is also expected to assist in undergraduate teaching.

The gross monthly salary will range from €2,222 in the first year to €2,840 in the last year. The Collective Labour Agreement (cao) for Dutch Universities is applicable.

What do we offer you?

Some of the things we have to offer:

  • a unique community of Data Science researchers;
  • a friendly and informal working environment;
  • a high-level of interaction;
  • a location in the city centre;
  • an international environment (10+ nationalities in the group);
  • access to high-end computing facilities (cluster with CPU 4,000+ cores and 50+ GPUs).

Since Amsterdam is a very international city where almost everybody speaks and understands English.

Additional information

Supervisors of the PhD project will be Prof. Marc Salomon, Dr Umut Konus, and Dr Jonne Guyt.

For further information, please contact:

Applications should be made via:

Please quote vacancy number 17-584 in the subject line.

All applications should include a:

  • curriculum vitae;
  • list of university courses taken with grades;
  • single page maximum statement of motivation and research interests.

An interview and a scientific presentation will be part of the selection process.


With over 5,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.

The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.

Amsterdam Business School

The Amsterdam Business School (ABS) is a partner of Amsterdam Data Science, a network consisting of the academic knowledge institutes in the Amsterdam Metropolitan Area, and worldwide industry partners that focus on stimulating research and education in Data Science. The ABS is part of the Faculty of Economics and Business (FEB).The FEB provides academic programmes for more than 5,500 students and employs about 400 people. The Faculty conducts research in many specialist areas and participates in the Tinbergen Institute, one of Europe's leading graduate schools in economics, finance and econometrics.