job – Python Predictions – data scientists.

Screenshot 2016-06-30 13.51.09

Hi Philippe,

We’re looking for some great new people again.
Would be great if you could give us some visibility for our search.
Candidates can simply send CV and (e)mail of motivation to jobs@pythonpredictions.com
More details in the links or text below
Thanks!!!
Geert
Data Scientist
Python Predictions – Bruxelles Woluwe-Saint-Pierre
Python Predictions is a Brussels-based consulting firm founded in 2006 and specialized in data science and predictive analytics. We are currently looking for data scientists.

Responsibilities

  • In-company data science projects for our clients
  • Contribute to explorative, descriptive and predictive analysis

Required skills or education

  • Proven interest and skills in data science and analytics
  • Proven interest and skills in at least one analytical programming language
  • Work flexibly in rapidly changing environments
  • Good visualisation and communication skills
  • Understand business problems

Personality

  • Analytical mindset
  • Open minded
  • Integrity
  • Critical of the output produced

Language skills

  • Working knowledge of Dutch, French and English

How to apply?
Send us your curriculum vitae and brief letter of motivation.We need both documents in order to consider your application.

More details
http://pythonpredictions.com/jobs/come-mine-with-us/

About us
Why should you apply for a position at Python Predictions? We believe we understand as no others what makes analysts tick. We believe that successful analysts must possess and develop a number of very distinct skills, ranging from social to technical, from intuitive to analytical. Putting these skills to work on real-life analytical projects is rewarding. And we provide a stimulating environment with focus on innovation and cooperation. Find our more about our activities on www.pythonpredictions.com

Job Type: Full-time

Required languages:

  • Dutch
  • English
  • French

Job – MDCPartners – Senior Data Engineer

Screenshot 2016-06-27 14.55.11

Job Requirements

About MDCPartners

MDCPartners is a technology company based in Antwerp, Belgium that produces large volumes of healthcare data on a weekly basis. This requires skilled techies with an eye for data, and the ability to apply this knowledge in the field of healthcare. Our clients are top pharma companies that rely on our tools to make crucial decisions during drug development.

Responsibilities

As Senior Data Engineer you work in the data lifting team to streamline and innovate data processing components and workflow. You deal with algorithmic, performance and operational tasks related to the main data flow in MDCPartners.

Your main target is to oversee parts of the data generation, improve quality of the data, the processing performance and downstream application possibilities by means of your architectural and algorithmic input.

Keywords: data analysis, algorithms, NLP, machine learning, Lucene, ontologies, medical data, performance, parallel programming

Requirements

  • Have a Master’s degree or PhD in Computer Science
  • Have at least 4 years of proven experience in the field
  • Have fantastic Java skills
  • Know your way around (No)SQL databases
  • Be fluent in English
  • Have a no-nonsense problem solving mindset
  • Be eager to take technical and organizational responsibility
  • Learn quickly, and want to be challenged
  • Have the ability to support and mentor other data engineers

What we offer

  • A hi-tech, creative working environment in a dynamic, growing company
  • Career path to grow to a crucial role
  • Competitive salary & benefits
  • Company car or similar remuneration options possible
  • Health insurance package

How to apply

For further information or to apply for this vacancy, please contact us and include your CV.

Apply:

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 datasciencebe@gmail.com .

For further information or to apply for this vacancy, please contact MDC and include your CV.

Analytics: Lessons Learned from Winston Churchill

chrurchill

I had the pleasure to be invited for lunch by Prof. Baessens earlier this week and we talked about a next meetup subject that could be ‘War and Analytics’. As you might know Bart  is a WWI fanatic and he has already written a nice article on the subject called ‘Analytics: Lessons Learned from Winston Churchill’

here is the article—

Nicolas Glady’s Activities

Activities Overview‎ > ‎Online articles‎ > ‎ Analytics: Lessons Learned from Winston Churchill

Analytics has been around for quite some time now.  Even during World War II, it proved critical for the Allied victory. Some famous examples of allied analytical activities include the decoding of the enigma code, which effectively removed the danger of submarine warfare, and the 3D reconstruction of 2D images shot by gunless Spitfires, which helped Intelligence at RAF Medmenham eliminate the danger of the V1 and V2 and support operation Overlord. Many of the analytical lessons learned at that time are now more relevant than ever, in particular those provided by one of the great victors of WWII, then Prime Minister, Sir Winston Churchill.

The phrase “I only believe in statistics that I doctored myself” is often attributed to him. However, while its wit is certainly typical of the Greatest Briton, it was probably a Nazi Propaganda invention. Even so, can Churchill still teach us something about statistical analyses and Analytics?

 

A good analytical model should satisfy several requirements depending upon the application area and follow a certain process. The CRISP-DM, a leading methodology to conduct data-driven analysis, proposes a structured approach: understand the business, understand the data, prepare the data, design a model, evaluate it, and deploy the solution. The wisdom of the 1953 Nobel Prize for literature can help us better understand this process.

Have an actionable approach: aim at solving a real business issue

Any analytics project should start with a business problem, and then provide a solution. Indeed, Analytics is not a purely technical, statistical or computational exercise, since any analytical model needs to be actionable. For example, a model can allow us to predict future problems like credit card fraud or customer churn rate. Because managers are decision-makers, as are politicians, they need “the ability to foretell what is going to happen tomorrow, next week, next month, and next year… And to have the ability afterwards to explain why it didn’t happen.” In other words, even when the model fails to predict what really happened, its ability to explain the process in an intelligible way is still crucial.

In order to be relevant for businesses, the parties concerned need first to define and qualify a problem before analysis can effectively find a solution. For example, trying to predict what will happen in 10 years or more makes little sense from a practical, day-to-day business perspective: “It is a mistake to look too far ahead. Only one link in the chain of destiny can be handled at a time.”  Understandably, many analytical models in use in the industry have prediction horizons spanning no further than 2-3 years.

Understand the data you have at your disposal

There is a fairly large gap between data and comprehension. Churchill went so far as to argue that “true genius resides in the capacity for evaluation of uncertain, hazardous, and conflicting information.”  Indeed, Big Data is complex and is not a quick-fix solution for most business problems. In fact, it takes time to work through and the big picture might even seem less clear at first. It is the role of the Business Analytics expert to really understand the data and know what sources and variables to select.

Prepare the data

Once a complete overview of the available data has been drafted, the analyst will start preparing the tables for modelling by consolidating different sources, selecting the relevant variables and cleaning the data sets. This is usually a very time-consuming and tedious task, but needs to be done: “If you’re going through hell, keep going.”

Never forget to consider as much past historical information as you can. Typically, when trying to predict future events, using past transactional data is very relevant as most of the predictive power comes from this type of information. “The longer you can look back, the farther you can look forward.”

read more here

Launching the first Data Science Bootcamp in Europe

We are so happy to launch the first European  data science bootcamp

It is so nice to write this page on the launch of the first European data science bootcamp that will start this summer in Brussels. This initiative will boost the digital transformation effort of each company by allowing them to improve their data skills either by recruiting trainees and young graduates or transforming existing BI teams to become experienced business data scientists.

Intense 5+12 weeks approach to focus on practical directly applicable business cases.

The content of this bootcamp originated from the Data Science Community. Following the advice of our academic,  innovation and training partners we have decided to offer a unique hands-on 5 + 12 weeks approach.

  1. We call the first 5 weeks the Summer Camp (starts Aug 16th).  The participants work onsite or remote on e-learning MOOCs from DataCamp to demonstrate their ability to code in Python, R, SAS, SQL and to master statistical principles. During this period experts put all their energy into coaching the candidates in keeping up the pace and finishing the exercises. All the activities take place in our training centre located in the European Data Innovation Hub.
    -> If you are a young graduate you can expect to be contacted by tier one companies who will offer you a job or traineeship that will start with the participation to the datascience bootcamp.
  2. The European Data Science Bootcamp starts September 19thDuring a 12 week period – every Monday and Tuesday – participants will work on 15 different business cases presented by business experts from different industries and covering diverse business areas. Each Friday, the future data scientists will gather to work on their own business case, with coaching by our data experts to achieve an MVP (Minimum Viable Product) at the conclusion of the bootcamp.

Delivering strong experienced business data science professionals after an intense semester of hands-on business cases.

Companies are invited to reserve seats for their own existing staff or for the young graduates who have expressed interest in following the bootcamp.

 Please reserve your seat(s) now as, this bootcamp is limited to 15 participants.

Please contact Nele Coghe on training@di-academy.com or click on di-Academy to learn more information about this first European Data Science Bootcamp.

  • Here  is the powerpoint presentation explaining the Bootcamp.
  • Here is the presentation done by Nele during the Data Innovation Summit.

Hope to see you soon at the Hub,

Philippe Van Impe
pvanimpe@di-academy.com

Seminar – June 22 – SAP Data, Finally With Zero Waiting Time

data_scientist

Getting access to data is always a high priority for all data scientists. Anyone delaying or blocking access to data is often regarded as ‘the enemy’. But when the data source is SAP the challenge takes on a whole new meaning with endless requirement forms and waiting times of geological proportions. Any data scientist in medium-to-large companies will inevitably face this humongous challenge with accessing SAP data.

But what if data scientists had access to all SAP data all the time ?

On 22-Jun, a “Free-Your-SAP-data” seminar will explain how to access all SAP data within days (not years), then let data pour in real-time to fuel science. This seminar will explain the underlying technology and share examples from several of the world’s most popular brands in the food, beverages and manufacturing industries.

Info & agenda :

  • 10h00 Introduction
  • 10h15 How to “free your SAP data”?
  • 11h00 Customer Cases:
    • Handling multiple SAP source systems
    • Integration with non-SAP data
  • 12h00 Networking Lunch

New Postgraduate Progamme in Big Data & Analytics at KU Leuven!

bigdata

Nice initiative

It’s probably no news to you: big data is all around us! Every minute, more than 3 million pieces of content are shared on Facebook, 4 million searches are executed by Google, and Amazon makes more than hundred thousand dollars in sales. This flood of data offers tremendous opportunities, though challenges as well. Gartner estimates that only 15% of organizations are able to exploit big data for competitive advantage, a strong indication of the upcoming need for analytical skills and resources.  As the data piles up, managing and analyzing this powerful resource in the best way become critical success factors in creating competitive advantage and strategic leverage.

Due to increasing demand, we are launching a new postgraduate programme: Big Data & Analytics in Business and Management.

This programme is a unique offering as its aim is to bridge the gap between technical concepts and business applications of big data and analytics techniques. The programme will discuss data analytics fundamentals and big data technologies, but also business applications and managerial aspects, such as dealing with team organization, data quality, deployment, valorization concerns and privacy aspects.
The programme is targeted at professionals with a minimum amount of work experience. It consists of 8 half-day classes, organized on Fridays from October 7 until December 2, 2016.

For more information and registrations, please visit our website.

Data Science Meetup about the Panama Papers with Mar Cabra

putin

There was a big crowd attending inspiring talk by Mar Cabra from ICIJ last Thursday at the Data Science Meetup at the VUBrussels.

mar cabraMar gave a whole new meaning to Messi data. This data was originally obtained from an anonymous source by reporters at the German newspaper Süeddeustche Zeitung, who asked ICIJ to organize a global reporting collaboration to analyze the files.

More than 370 reporters in nearly 80 countries probed the files for a year. Their investigations uncovered the secret offshore holdings of 12 world leaders, more than 128 other politicians and scores of fraudsters, drug traffickers and other criminals whose companies had been blacklisted in the US and elsewhere.

Here is the link to her presentation.

The data is available and can be downloaded ! users are now able to search through the data and visualize the networks around thousands of offshore entities, including, when available, Mossack Fonseca’s internal records of the company’s true owners. The interactive database  also includes information about more than 100,000 additional companies that were part of the 2013 ICIJ Offshore Leaks investigation.

Try it yourself and download the database:

Some interesting links:

We were very happy that she could come to do this for our community. Although we did not record the presentation, here are two videos for info:

How the ICIJ Used Neo4j to Unravel the Panama Papers – Mar Cabra
https://www.youtube.com/watch?v=S20XMQyvANY
(very similar to last night, from GraphConnect Europe in London on 26th April);

The Making of a Scoop – The Panama Papers (W.Krach,
Süddeutsche Zeitung & K.Auletta) | DLDnyc 16
https://www.youtube.com/watch?v=_Yfq1gwAQZE

 

 

 

The Panama Papers is a global investigation into the sprawling, secretive industry of offshore that the world’s rich and powerful use to hide assets and skirt rules by setting up front companies in far-flung jurisdictions.
Based on a trove of more than 11 million leaked files, the investigation exposes a cast of characters who use offshore companies to facilitate bribery, arms deals, tax evasion, financial fraud and drug trafficking.
Behind the email chains, invoices and documents that make up the Panama Papers are often unseen victims of wrongdoing enabled by this shadowy industry.

Don’t miss the prep meeting 3/6 tonight with the experts from Euroclear !

prep 3.png

DON’T Miss the 3rd/6 evening of preparation for the Text Mining hackathon (17/6) it is probably the most important one.
Tonight the experts of Euroclear will explain how they do Text mining and the business experts will be there to assist you and explain the dataset you have received to prepare yourself.

more info:
http://www.meetup.com/Brussels-Data-Science-Community-Meetup/events/231040266/

Next preparation meetings:

  • 1/6 – Euroclear
  • 8/6 – SAS mining technologies
  • 9/6 – Python’s NLTK
  • 15/6 closer look at Timi

BeneLearn 2016: Big Data Workshop – Machine Learning Meeting

BeneLearn is de jaarlijkse Machine Learning Conferentie van België en Nederland.

Deze 25e editie is een forum voor zowel onderzoekers als professionelen uit bedrijven om ideeën uit te wisselen, nieuw werk te presenteren en samenwerking te stimuleren in het brede veld van Machine Learning en toepassingen.

Programma

Maandag 12 september: Big Data Workshop

  • Keynote speakers: Jeffrey Ullman (Stanford Infolab), Isaac Triguero (UGent, University of Nottingham), Hugo Ceulemans (Janssen R&D)en Kristian Kersting (TU Dortmund)
  • Workshop “Big data in practice”
  • Presentaties door bedrijven
  • Conference Dinner

Dinsdag 13 september: BeneLearn Meeting

  • Keynote speakers: Greg Tsoumakas (Aristotle University of Thessaloniki), Emilia Barakova (Technische Universiteit Eindhoven), Christian Blum (University of the Basque Country)en Luc De Raedt (KU Leuven)
  • Mondelinge en posterpresentaties

Organisatie

De 25e editie wordt georganiseerd door KU Leuven, UGent en het Vlaamse Supercomputer Centrum.

Met ondersteuning door de School for Innovation and Knowledge Systems (SIKS)

Sponsoring
Uw bedrijf in de kijker zetten op deze conferentie kan via onze mogelijkheden voor sponsoring.

Praktisch

Data en locatie
Maandag 12 en dinsdag 13 september 2016

KU Leuven Campus Kulak Kortrijk, E. Sabbelaan 53 – B-8500 Kortrijk

Inschrijven

* tot en met 12 juli 2016

Academici
2 daags congres: 100 euro
1 daags congres: 60 euro

Professionelen
2 daags congres: 200 euro
1 daags congres: 120 euro

* Vanaf 13 juli 2016

Academici
2 daags congres: 150 euro
1 daags congres: 90 euro

Professionelen
2 daags congres: 300 euro
1 daags congres: 180 euro

Networking event – diner in Kortrijk op maandagavond 12 september: 50 euro

Inschrijven

Inschrijven kan online via het inschrijvingsformulier .

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