The Data Analytics Laboratory within the Business Technology & Operations (BUTO) department at the Faculty of Economic and Social Sciences and Solvay Business School is looking for a highly motivated candidate with strong abilities and interest to perform research in the field of data analytics for carrying out a research project in close collaboration with a company, with the aim to obtain a Ph.D. degree in Applied Economics.

The topic of the research project concerns the development of a framework for integrating data analytics applications and the development of profit-driven data analytics to support customer relationship management, with the aim to optimize customer lifetime value, by analysing large amounts of structured customer interaction data, marketing campaign data and financial information. By integrating various types of analyses and predictions, the aim is to provide detailed and actionable insight and feedback for optimized managerial decision-making.

The candidate is expected to conceptually develop and implement these applications by analysing available real-life data in close collaboration with and at location of the involved company. The project will require a thorough study of analytical approaches as well as the specific field of application. Upon successful realization of the project, the candidate will dispose of a strong theoretical knowledge as well as practical experience in applying and implementing analytics projects within a company setting.

The Data Analytics Laboratory is a vibrant research team of data scientists which actively engage in research projects with the industry for developing innovative business applications of Big Data Analytics. For more information, visit


Teaching exercises related to the course Statistics II for economic sciences to bachelor students.
Supervising bachelor paper and master thesis projects.
The teaching assignment relates to the research project, and will allow the candidate to reinforce his/her background knowledge on basic statistical principles, underlying the more advanced data analytical approaches.


The candidate will have to assist in surveying the computer rooms (one evening per week, 16h-20h).


Place of employment: Brussels (VUB, campus Etterbeek). For more information, please contact Wouter Verbeke: +32 629 20 53 or


The candidate has an academic Master degree in Engineering, Computer Science, Business Engineering, Applied Economics, Applied Sciences or Sciences (e.g. Mathematics, Informatics, etc.), and combines strong quantitative and problem solving skills with a profound interest in business and management.

Excellent written and spoken knowledge of Dutch and English.

Preferably, the candidate possesses the following skills and knowledge:

Knowledge of data analysis (statistics, analytics, machine learning)
Programming skills (e.g., R, Matlab, SAS, Python, Java)
Strong communication skills verbal and written (essential!)


As an employee of the Vrije Universiteit Brussel your days will be spent in a dynamic, diverse and multilingual environment. Both our campuses are set within green oases on the outskirts of the centre of the capital of Flanders, Belgium and Europe. This centre, with all its opportunities, is within your reach by public transport in under half an hour.

Depending on your experience and academic merits you will receive a salary on one of the pay scales laid down by the government. Hospitalisation cover and free use of public transport for travel to and from work are standard conditions of employment. If you would rather cycle to work, compensation is also available for that. Both campuses have extensive sporting facilities which are at your disposal and a nursery is within walking distance.
More information is available at under the heading “future employees”.

Additional information

  • Planned starting date: 01/12/2017
  • Length of contract: 1 year, initially, extendable upon positive evaluation
  • Deadline for application: 31/11/2017
  • Contact person Wouter Verbeke
  • Contact telephone +32 2 629 20 53
  • Contact e-mail
  • Applications can be submitted directly by contacting or online via the website of the Vrije Universiteit Brussel

All applications must at least include the following attachments:

  • A CV
  • A concise motivation of the reason for applying including relevant experience (research activities, study stays etc.)
  • A copy of the master degree

Data Analysis Internship at a political party

One of the participants at the Summer Coding Camp sent us this opening from his organisation:

The Brussels-based ALDE Party is seeking for a Data Analysis trainee for a 6 month period. The candidate should have a background in Statistics or Computer Science, or from the fields of Economics, Political Science, Psychology, or Sociology, with strong quantitative abilities.

More details can be found here:

Please feel free to share this opportunity!

Sundar Singaravel- Ignite Speaker at DIS 2017

Sundar Singaravel obtained a Master in Sustainable Energy Technology from the Eindhoven University of Technology, dis17_speaker_sundar-swhere he specialised in the area of Building Performance Simulation (BPS). He continued working in the building sector for about four years, developing design strategies for energy performance, natural ventilation, indoor comfort and fire safety. Strategies developed were for both building systems/installations and building design located in Netherlands, Ireland, Dubai, Qatar and India. He is currently working as a PhD researcher in the Department of Architectural Engineering, researching on a Machine Learning Method suitable for design stage application to predict building energy.

Follow him on Twitter here and join his Ignite speech “Application of machine learning models for sustainable building design” at DIS 2017.

Announcing Dr. Kirk Borne – Keynote Speaker at diSummit 2017

Dr. Kirkdis17_speaker_kirk-borne Borne is the Principal Data Scientist at
Booz | Allen | Hamilton (since 2015). He previously spent 12 years as Professor of Astrophysics and Computational Science at George Mason University where he taught and advised students in the Data Science program. Before that, he worked 18 years supporting NASA projects in various roles, including Program Manager in NASA’s Space Science Data Operations Office & Data Archive Project Scientist for
screen-shot-2017-03-02-at-12-20-29the Hubble Space Telescope.   He has a PhD in Astronomy
from the California Institute of Technology and a BS in Physics from Louisiana State University. He is an active contributor on social media, where he is an advocate of data literacy for all and has been named consistently every year since 2013 as the top worldwide influencer in big data and data science. In 2014 he was named an IBM Big Data and Analytics Hero. In 2016 he was named Fellow of the International Astrostatistics Association.

You can follow him on Twitter at @KirkDBorne
You can follow Booz | Allen | Hamilton on Twitter at @BoozAllen
Watch his TED talk on  Big Data, Small World

Here is a very interesting  video interview:
Here are some of his audio interviews (podcasts):
Join his C-level workshop on the 29th of March or come and see his speech at diSummit on the 30th of March 2017 at the ING Marnix building, Troonstraat 1, 1000, Brussels.

Looking for the insights on how to use data for good? Join the DATA NETWORKING EVENT of the year, the #dataforgood event in Belgium!

Looking for the insights on how to use data for good? Join the DATA NETWORKING EVENT of the year in Belgium!  Buy your tickets here.

Job – AXA – Marketing Data Analyst – Antwerp


Chez AXA Bank Europe, vous vous retrouvez dans une banque qui est en train de se repositionner et dont le slogan est: “AXA Banque – la banque toujours plus proche de vous”. Nous sommes tout à fait convaincus que nous réussirons et que nous conserverons une bonne place comme challenger sur le marché belge qui se focalise sur une offre simple et transparente de produits d’épargne (6ème du marché belge) et de crédits-logement (5ème du marché belge) pour particuliers. Avec moins de produits mais avec des produits meilleurs et des outils en ligne conviviaux. Soutenue par un réseau puissant de plus de 700 agents bancaires AXA locaux, indépendants et fortement ancrés.
AXA Banque est un acteur financier important en Belgique. Nous partageons les mêmes valeurs que les collègues des assurances et nous collaborons étroitement pour imposer au maximum la marque AXA et nos produits.
Chez AXA Banque, vous vous retrouvez dans un environnement de travail dynamique, avec des collaborateurs qui aiment les défis. L’approche se résume en un mot de 4 lettres: FAST – fair, attentive, simple & transparent. Quatre mots qui expriment la stratégie d’AXA Banque, mais aussi notre culture d’entreprise. Fair dans la gestion du personnel de la Banque; attentive, car le client occupe pour nous une place centrale; simple, car la simplicité et la simplification sont au coeur de notre travail quotidien; transparent pour la communication honnête et directe.

Job description:

En tant qu’analyste de données marketing, vous dirigez le développement et l’introduction d’outils et de méthodes pour l’analyse de portefeuilles. Vous analysez et identifiez des segments pouvant maximaliser le taux de réponse, la croissance et la rentabilité des diverses campagnes de marketing.

  • Vous soutenez l’équipe de marketing stratégique dans l’optimalisation et la segmentation des actions commerciales de marketing ;
  • Vous collaborez dans la même équipe avec les collègues analystes de campagnes, dans l’amélioration permanente du plan de contact marketing.
  • Vous utilisez des techniques d’exploration de données (« Data Mining ») pour explorer les diverses sources de données (base de données de clients, site Web, données de campagnes) et en tirer des conclusions ;
  • Vous peaufinez continuellement les méthodes et les outils de pilotage marketing et de renseignements clients ;
  • Vous livrez des chiffres et des rapports fiables et vous réalisez des analyses pertinentes sur les différentes actions marketing.

Candidates Profile:

  • Vous avez une formation supérieure (de niveau mastère) de préférence dans le domaine de l’économie, de la statistique, des mathématiques, l’ingénierie (commerciale), etc.
  • Vous pouvez mettre en avant une expérience de 3 à 5 ans dans une fonction similaire
  • Vous avez une solide connaissance des logiciels d’analyse des données et des outils d’analyse Web (SAS, Teradata, Excel, R, SQL, Google Analytics) ;
  • Vous avez un esprit analytique marqué et êtes motivé par la recherche de relations et de nouvelles interprétations
  • Vous pouvez travailler de manière autonome, mais aussi en équipe ; vous êtes résistant au stress
  • Votre travail est précis et vous avez le souci du détail
  • Votre langue maternelle est le néerlandais ou le français et vous possédez une bonne connaissance de la deuxième langue nationale


Make sure that you are a member of the Brussels Data Science Community linkedin group before you apply. Join  here.

Please note that we also manage other vacancies that are not public, if you want us to bring you in contact with them too, just send your CV to .

Here is the link to the original job add.

Please Apply Online

Job – KULeuven – 4-year PhD position – Fundamental Atomic Data deduced from Stellar Spectroscopy


The Instituut voor Sterrenkunde of Leuven University has a 4-year PhD position; Fundamental Atomic Data deduced from Stellar Spectroscopy.
The Institute of Astronomy (IoA) of KU Leuven is a young and active research group of some 50 scientists, engineers and administrative staff ( The institute is involved in several international networks and research projects that rely on data gathered with telescopes at international observatories and with space missions. The institute is also responsible for the organization of the Master in Astronomy & Astrophysics of the Faculty of Science at Leuven University.
With this vacancy, we are looking for a motivated PhD student to join the IvS to pursue a research program aiming at a. produce a reference catalog of high-resolution stellar spectroscopy from a large amount of data (existing in house). b model these spectra and compare them with the observations in order to critically assess the quality of existing databases of fundamental atomic parameters.
This research program will be conducted in collaboration between the KU Leuven and the Royal Observatory of Belgium. The student will have the opportunity to share his/her time between the two institutions and to collaborate with specialists of very different observational as well as theoretical backgrounds.


Accurate atomicline transition data are fundamental input parameters in astrophysics. They are central for the development of complex models that try to describe stars, their internal structures, atmospheres and evolution in relation to the stellar environment. Uncertainties and errors in adopted fundamental atomic data may systematically propagate throughout all fields of astrophysics, from star formation to galactic evolution.

It is very difficult to obtain accurate fundamental atomic data of astrophysical interest from laboratory measurements, and important quality assessments of the provided atomic data are scarce. This very much complicates the validation of results that follow from their application.

The current project aims at taking a first, although crucial, step towards removing systematic errors in atomic input data required for quantitative stellar spectroscopy. To reach this goal, we will compare very high-quality observed stellar spectra with state-of-the-art theoretical spectra. Although the observations are still ongoing, a very large collection of high-resolution spectroscopic data already exists.

The first goal of the project is to produce a uniform catalog of very high quality spectra and spectral templates from these data. This catalog will be made available to the entire astronomical community. We expect it to be used for various purposes by the astronomical community, offering the student many opportunities for collaborations.

In a second step, the main goal of the thesis will be addressed by comparing the spectra to state-of-the-art spectral modeling in order to retrieve the fundamental atomic parameters. Finally, these measurements will allow a critical assessment of the quality of the information offered by the various atomic repositories.


 The candidate

  • has a Master diploma in Astrophysics, Physics or Mathematics
  • has good knowledge of the English language
  • some coding experience is an asset


The initial contract is for two years and, following standard practice at KU Leuven, shall be prolonged with another two years after positive evaluations.The starting date will be 1 September 2015. The net monthly salary is according to the governmental regulations and depends on the applicant’s work experience but is not less than 1800 Euro (pocket salary). The applicants will be required to receive approval from the Arenberg Doctoral School of the KU Leuven prior to the start of the PhD.


Make sure that you are a member of the Brussels Data Science Community linkedin group before you apply. Join  here. Please note that we also manage other vacancies that are not public, if you want us to bring you in contact with them too, just send your CV to .

Applications must be submitted via the online application tool: URL. Upload a Curriculum Vitae, scores of all finished master courses so far, the names and email addresses of two reference persons, and a one-page motivation letter, all in a single PDF file.
For more information please contact Dr. Katrijn Clémer, tel.: +32 16 32 70 40, mail:
You can apply for this job no later than April 15, 2015 via the
Downloads :pdf


Competition – Kaggle – AXA – Use telematic data to identify a driver signature

kaggle-logo-transparent-300 & Axa

In case you are  looking for data to work on …

here is a nice Kaggle competition for you.


For automobile insurers, telematics represents a growing and valuable way to quantify driver risk. Instead of pricing decisions on vehicle and driver characteristics, telematics gives the opportunity to measure the quantity and quality of a driver’s behavior. This can lead to savings for safe or infrequent drivers, and transition the burden to policies that represent increased liability.

AXA has provided a dataset of over 50,000 anonymized driver trips. The intent of this competition is to develop an algorithmic signature of driving type. Does a driver drive long trips? Short trips? Highway trips? Back roads? Do they accelerate hard from stops? Do they take turns at high speed? The answers to these questions combine to form an aggregate profile that potentially makes each driver unique.

For this competition, Kaggle participants must come up with a “telematic fingerprint” capable of distinguishing when a trip was driven by a given driver. The features of this driver fingerprint could help assess risk and form a crucial piece of a larger telematics puzzle.

Started: 2:00 pm, Monday 15 December 2014 UTC
Ends: 11:59 pm, Monday 16 March 2015 UTC (91 total days)
Points: this competition awards standard ranking points
Tiers: this competition counts towards tiers

Summit- Data Innovation – Call for sponsors

datascience Innovation

One full day to get the full picture of data innovation made in Belgium.

We expect 500 participants.

The full panel of the Belgian Data Innovative Power will be present.

The agenda is available here.

Over 30 presentations will  be streamed live and recorded.

The best cases will be bundled in a book.

In order to cover the catering and  organisation costs of this event, we have decided to call upon the support of our future partners.

Different sponsoring options are possible. Please contact Philippe for more details. ( – 0477/23.78.42)