Job – Junior Data Scientist

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Are you pursuing a career in data science?

We have a great opportunity for you: an intensive training program combined with interesting job opportunities!

Interested? Check out http://di-academy.com/bootcamp/ follow the link to our datascience survey and send your cv to training@di-academy.com

Once selected, you’ll be invited for the intake event that will take place in Brussels this summer.

Hope to see you there,

Nele & Philippe

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.

Manufacturing Sustainability Hackathon – P&G

Bigdata Manufacturing Sustainability Hackathon

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Partner with us and Pioneer the new benefits of bigdata and datascience to help us Preserve our environment.

Interested ?

  • We provide 1 year of process data
  • Using your data science skills, help us make our plants greener
  • Compete to win one of these 3 challenges :
    1. Green dashboard,
    2. Sustainability Predictive model, 
    3. Out-of-the-box Sustainability concept

What you need to do

5E34C4DBF74C0CC27FBF30D0ED58729BApply and RSVP on our meetup page for the kick off event in the afternoon of February 26th.

About P&GDC0EDB259D99B454FCE1BEE3A509DC17

P&G serves consumers around the world with one of the strongest portfolios of trusted, quality, leadership brands, including Always®, Ambi Pur®, Ariel®, Dash®, Gillette®, Head & Shoulders®, Lenor®, Olaz®, Oral-B®, Pampers® and Pantene®. The P&G community includes operations in approximately 70 countries worldwide.

The P&G Brussels Innovation Center hosts the biggest Fabric & Home Care R&D facility for P&G in Europe.

A Company of Leading Brands

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Across our ten categories, P&G has 21 brands with annual sales of $1 billion to about $10 billion, and 11 brands with sales of $500 million to $1 billion – many of those with billion-dollar potential.

Please visit http://www.pg.com for the latest news and information about P&G and its brands.

Sustainability at P&G

P&G is committed to touching and improving lives in a way that preserves and protects the planet. We have established a long-term vision which can only be achieved by setting short-term goals to ensure we stay on track.

We want people who choose P&G brands to know that our products are created with a commitment to sustainability. From formulation to manufacturing to package design and shipment, our products are made responsibly and without trade-offs in performance or value.

Our approach to bring our strategies to life and accelerate progress is to Preserve, Partner and Pioneer.

We Preserve

preserveWe are working to use less while doing more by reducing our environmental footprint and increasing our positive impact on the communities we serve.

Our Pampers teams in Western Europe cut packaging by 80% by moving from “box-to-bag” packaging, saving 6,000+ tons of material, 430+ truckloads and 160+ tons of CO2 emissions per year.

In the last 20 years, Pampers has reduced 50% of the weight of each diaper and 70% of the external packaging.

We Partner

partnerWe can accomplish more with partners than we can alone.

P&G plans to meet its North America electricity demands by using 100 percent wind power to make iconic Fabric & Home Care brands, such as Tide and Dawn. This is possible thanks to a new partnership with EDF Renewable Energy (EDF RE) which will see a new Texas based wind farm generate 370,000 MWh of electricity each year. The wind farm will be fully operational in December 2016.

With support of more than 150 global partners, our key corporate cause, The P&G Children’s Safe Drinking Water (CSDW) Program, marked its tenth year supporting families and children in some of the most remote parts of the world with clean drinking water.

We Pioneer

pioneerWe aim to improve tomorrow through industry-leading innovation.

We are turning agricultural corn waste into a key cleaning ingredient for Tide Coldwater. Working with DuPont, we developed a breakthrough process that will turn 7,000 tons of agricultural waste annually into cellulosic ethanol. Tide Coldwater is the first brand in the world on a path to blend cellulosic ethanol in a scalable and commercial way.

For more details on our sustainability goals and progress, please go to www.pg.com/en_US/sustainability/report.shtml.

Event – DIS2016 – Data Innovation Summit – March 23rd – AXA Brussels

#DIS2016 – AXA building – Brussels – March 23rd.
Reserve your seat: 
https://dis2016.eventbrite.co.uk

Datascience innovation summit

The main theme will be: “Digital Transformation”

Last year’s success motivated us to hold The Data Innovation Summit again in the AXA building in Brussels.

We expect over 500 visitors interested in #DataInnovation, #DataScience, #BigData coming from the public, academic, business and startup world.

We will have less presentations than last year and provide you with more time to network and have one-to-one sessions.

Registration:

Reserve your seat now for DIS2016 – 23rd March 2016 Brussels.

Registration fee starts at just over 25€ if you are an early bird, you finalise the survey and share your enthusiasm with on your linkedin account…

Agenda:

agenda

parallel tracks

The list of exhibitors, partners and sponsors is available here.

#DIS2016 – Survey

servetten-100-euro-geld

  • You will get 100€ discount when :

– you respond to the survey.
– share your enthusiasm in a Linkedin post

Possible discounts:

Contact ophelie.datascience@gmail.com to request your discount

  1. Unemployed professionals and carreer switchers get 75% discount
  2. Active members of the community who have done presentations at other meetups or shared their knowledge in trainings and coaching sessions get 50%
  3. Co-workers and startups hosted at the HUB get also 50% discount

Partnering with this event:

We welcome partners, you can review the sponsoring options here.

Remember DIS2015:

  • Here are some of the videos of last year’s event.
  • Some pictures of last year’s event

 

 

The essence of Predictive Analytics for Managers – Executive Training

Creating more business value from investments in Big Data and Predictive Analytics through better project definition, project management and better usage of Predictive Analytics projects.

Target audience

Managers of analytical teams, Managers of functional departments (marketing, risk, operations, HR,…), Project managers, CxO.

Details

  • Duration: One afternoon workshop (4h):
    • December 3rd, 2015
  • Location: European Data Innovation Hub @ AXA, Vorstlaan 23, 1170 Brussel
  • Price: 570€ per manager
  • Limited from 8 – 12 participants

Registration:

Please register using Eventbrite following this link.

Motivation:

Fueled by the energy around Big Data projects, an increasing number of managers are attracted to the domain of Big Data and advanced analytics. When successfully applied, analytics provides the key to turn data into big value. Typical goals of such high-impact projects involve:

(i) increase targeted marketing success by predicting response

(ii) increase marketing relevance by offering the right product to the right client,

(iii) decrease risk exposure by predicting credit or fraud risk,

(iv) increase process efficiency,

(v) retain crucial staff members, etc.

Overview:

This training provides a backbone for managing projects in Predictive Analytics that maximally impact the organisation. Put differently, in this workshop we ensure participants reap the maximum return on their analytical investments. Additionally, this training establishes the foundation for fruitful collaboration between analysts, their peers and decision makers.

The workshop is designed as an interactive learning experience packed with best practices illustrated with real domain experience.

Learning objectives:

After the training, participants will be able to define and manage developments in Predictive Analytics. In practice participants will be able to

  • Explain the crucial phases needed to engage in projects in predictive analytics
  • Define a project in predictive analytics in detail, using a concise project definition checklist
  • Understand the essential principles for predictive analytics and why they matter to management
  • Understand the requirements and limitations of predictive analytics
  • Fully understand the output of predictive analytics to increase their impact on the organizational goals

 

Prerequisites:

Before the start of the first session, participants should attempt to define a practical and relevant project within their organisation. At completion of the workshop, it is the aim that managers will be able to further define and understand the steps needed to manage this challenge to success.

 Geert Verstraeten

About the trainer:

Geert Verstraeten (PhD) is a dynamic trainer with a solid background both in predictive analytics and in professional training. Geert has 14 years of experience in building predictive models for organisations in a wide array of industries. Additionally, he has 14 years of academic and industry experience
in training and coaching managers and analysts to succeed with Predictve Analytics. Since 2006, he is managing partner at Python Predictions (www.pythonpredictions.com), a Brussels-based niche player in Predictive Analytics, and was involved in building analytical communities both in Belgium and abroad. Geert is a frequent speaker at academic and business conferences in analytics. Since 2014, Geert is a certified professional trainer.

Certification:

Attendees receive an electronic version of the handouts and a proof of participation at the conclusion of the workshop.

The ABC of Datascience blogs – collaborative update

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A – ACID – Atomicity, Consistency, Isolation and Durability

B – Big Data – Volume, Velocity, Variety

C – Columnar (or Column-Oriented) Database

  • CoolData By Kevin MacDonell on Analytics, predictive modeling and related cool data stuff for fund-raising in higher education.
  • Cloud of data blog By Paul Miller, aims to help clients understand the implications of taking data and more to the Cloud.
  • Calculated Risk, Finance and Economics

D – Data Warehousing – Relevant and very useful

E – ETL – Extract, transform and load

F – Flume – A framework for populating Hadoop with data

  • Facebook Data Science Blog, the official blog of interesting insights presented by Facebook data scientists.
  • FiveThirtyEight, by Nate Silver and his team, gives a statistical view of everything from politics to science to sports with the help of graphs and pie charts.
  • Freakonometrics Charpentier, a professor of mathematics, offers a nice mix of generally accessible and more challenging posts on statistics related subjects, all with a good sense of humor.
  • Freakonomics blog, by Steven Levitt and Stephen J. Dubner.
  • FastML, covering practical applications of machine learning and data science.
  • FlowingData, the visualization and statistics site of Nathan Yau.

G – Geospatial Analysis – A picture worth 1,000 words or more

H – Hadoop, HDFS, HBASE

  • Harvard Data Science, thoughts on Statistical Computing and Visualization.
  • Hyndsight by Rob Hyndman, on fore­cast­ing, data visu­al­iza­tion and func­tional data.

I – In-Memory Database – A new definition of superfast access

  • IBM Big Data Hub Blogs, blogs from IBM thought leaders.
  • Insight Data Science Blog on latest trends and topics in data science by Alumnus of Insight Data Science Fellows Program.
  • Information is Beautiful, by Independent data journalist and information designer David McCandless who is also the author of his book ‘Information is Beautiful’.
  • Information Aesthetics designed and maintained by Andrew Vande Moere, an Associate Professor at KU Leuven university, Belgium. It explores the symbiotic relationship between creative design and the field of information visualization.
  • Inductio ex Machina by Mark Reid’s research blog on machine learning & statistics.

J – Java – Hadoop gave it a nice push

  • Jonathan Manton’s blog by Jonathan Manton, Tutorial-style articles in the general areas of mathematics, electrical engineering and neuroscience.
  • JT on EDM, James Taylor on Everything Decision Management
  • Justin Domke blog, on machine learning and computer vision, particularly probabilistic graphical models.
  • Juice Analytics on analytics and visualization.

K – Kafka – High-throughput, distributed messaging system originally developed at LinkedIn

L – Latency – Low Latency and High Latency

  • Love Stats Blog By Annie, a market research methodologist who blogs about sampling, surveys, statistics, charts, and more
  • Learning Lover on programming, algorithms with some flashcards for learning.
  • Large Scale ML & other Animals, by Danny Bickson, started the GraphLab, an award winning large scale open source project

M – Map/Reduce – MapReduce

N – NoSQL Databases – No SQL Database or Not Only SQL

O – Oozie – Open-source workflow engine managing Hadoop job processing

  • Occam’s Razor by Avinash Kaushik, examining web analytics and Digital Marketing.
  • OpenGardens, Data Science for Internet of Things (IoT), by Ajit Jaokar.
  • O’reilly Radar O’Reilly Radar, a wide range of research topics and books.
  • Oracle Data Mining Blog, Everything about Oracle Data Mining – News, Technical Information, Opinions, Tips & Tricks. All in One Place.
  • Observational Epidemiology A college professor and a statistical consultant offer their comments, observations and thoughts on applied statistics, higher education and epidemiology.
  • Overcoming bias By Robin Hanson and Eliezer Yudkowsky. Present Statistical analysis in reflections on honesty, signaling, disagreement, forecasting and the far future.

P – Pig – Platform for analyzing huge data sets

  • Probability & Statistics Blog By Matt Asher, statistics grad student at the University of Toronto. Check out Asher’s Statistics Manifesto.
  • Perpetual Enigma by Prateek Joshi, a computer vision enthusiast writes question-style compelling story reads on machine learning.
  • PracticalLearning by Diego Marinho de Oliveira on Machine Learning, Data Science and Big Data.
  • Predictive Analytics World blog, by Eric Siegel, founder of Predictive Analytics World and Text Analytics World, and Executive Editor of the Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating.

Q – Quantitative Data Analysis

R – Relational Database – Still relevant and will be for some time

  • R-bloggers , best blogs from the rich community of R, with code, examples, and visualizations
  • R chart A blog about the R language written by a web application/database developer.
  • R Statistics By Tal Galili, a PhD student in Statistics at the Tel Aviv University who also works as a teaching assistant for several statistics courses in the university.
  • Revolution Analytics hosted, and maintained by Revolution Analytics.
  • Rick Sherman: The Data Doghouse on business and technology of performance management, business intelligence and datawarehousing.
  • Random Ponderings by Yisong Yue, on artificial intelligence, machine learning & statistics.

S – Sharding (Database Partitioning)  and Sqoop (SQL Database to Hadoop)

  • Salford Systems Data Mining and Predictive Analytics Blog, by Dan Steinberg.
  • Sabermetric Research By Phil Burnbaum blogs about statistics in baseball, the stock market, sports predictors and a variety of subjects.
  • Statisfaction A blog by jointly written by PhD students and post-docs from Paris (Université Paris-Dauphine, CREST). Mainly tips and tricks useful in everyday jobs, links to various interesting pages, articles, seminars, etc.
  • Statistically Funny True to its name, epidemiologist Hilda Bastian’s blog is a hilarious account of the science of unbiased health research with the added bonus of cartoons.
  • SAS Analysis, a weekly technical blog about data analysis in SAS.
  • SAS blog on text mining on text mining, voice mining and unstructured data by SAS experts.
  • SAS Programming for Data Mining Applications, by LX, Senior Statistician in Hartford, CT.
  • Shape of Data, presents an intuitive introduction to data analysis algorithms from the perspective of geometry, by Jesse Johnson.
  • Simply Statistics By three biostatistics professors (Jeff Leek, Roger Peng, and Rafa Irizarry) who are fired up about the new era where data are abundant and statisticians are scientists.
  • Smart Data Collective, an aggregation of blogs from many interesting data science people
  • Statistical Modeling, Causal Inference, and Social Science by Andrew Gelman
  • Stats with Cats By Charlie Kufs has been crunching numbers for over thirty years, first as a hydrogeologist and since the 1990s, as a statistician. His tagline is- when you can’t solve life’s problems with statistics alone.
  • StatsBlog, a blog aggregator focused on statistics-related content, and syndicates posts from contributing blogs via RSS feeds.
  • Steve Miller BI blog, at Information management.

T – Text Analysis – Larger the information, more needed analysis

U – Unstructured Data – Growing faster than speed of thoughts

V – Visualization – Important to keep the information relevant

  • Vincent Granville blog. Vincent, the founder of AnalyticBridge and Data Science Central, regularly posts interesting topics on Data Science and Data Mining

W – Whirr – Big Data Cloud Services i.e. Hadoop distributions by cloud vendors

X – XML – Still eXtensible and no Introduction needed

  • Xi’an’s Og Blog A blog written by a professor of Statistics at Université Paris Dauphine, mainly centred on computational and Bayesian topics.

Y – Yottabyte – Equal to 1,000 exabytes, 1 million petabytes and 1 billion terabytes

Z – Zookeeper – Help managing Hadoop nodes across a distributed network

Feel free to add your preferred blog in the comment bellow.

Other resources:

Nice video channels:

More Jobs ?

hidden-jobs1

Click here for more Data related job offers.
Join our community on linkedin and attend our meetups.
Follow our twitter account: @datajobsbe

Improve your skills:

Why don’t you join one of our  #datascience trainings in order to sharpen your skills.

Special rates apply if you are a job seeker.

Here are some training highlights for the coming months:

Check out the full agenda here.

Join the experts at our Meetups:

Each month we organize a Meetup in Brussels focused on a specific DataScience topic.

Brussels Data Science Meetup

Brussels, BE
1,417 Business & Data Science pro’s

The Brussels Data Science Community:Mission:  Our mission is to educate, inspire and empower scholars and professionals to apply data sciences to address humanity’s grand cha…

Next Meetup

DATA UNIFICATION IN CORPORATE ENVIRONMENTS

Wednesday, Oct 14, 2015, 6:30 PM
57 Attending

Check out this Meetup Group →

Event – Official Opening of the European Data Innovation Hub in Brussels – October 20th 10AM

HUBdatainnovation invitation

We are so pleased to announce that our Hub will officially be inaugurated by Alexander De Croo, Bianca Debaets, Frank Koster, Marietje Schaak and Jörgen Gren. Over 100 directors and managers have already confirmed their presence to this ribbon cutting ceremony that will be held in our new offices in the Axa building.

266px-Alexander_de_croo_675 bianca-in-brussel frank marietjejorgen_gren

Join us on October 20th at 10AM to meet young data startups, talk to representatives of the academic world, share your ideas with the politics representatives that support us and discover our datascience training offering.

There are only a few more spaces left so please hurry and reserve your seat via our eventbrite page.

I’m looking forward to meeting you in our new offices soon,

Philippe Van Impe
asbl European Data Innovation Hub vzw 
Inspire – Innovate – Connect

Job – KBC – Junior data scientist

logo_kbc

What will your responsibilities be? 

In a changing market environment, where customer needs are more diverse and customer expectations are more personalized, KBC group wants to optimally use the growing “data footprint” of the market to become more customer centric and become a reference in data analytics. Ultimately, we aim to transform our business into a data driven group. KBC therefore wants to attract capabilities that are highly advanced in exploiting, analysing and modelling data.

What do we expect from you? 

  • Feeding local Business Units with unknown insights based on data and assisting them with the commercial activation of these insights
  • Analytical work on a portfolio of initiatives
  • Testing commercial hypothesis as suggested by Business Units or from within the own group
  • Becoming the reference for Big Data expertise within the Group with regards to Data Analysis & Modelling

Location 

Louvain, with regular trips to other KBC headquarters internationally.

What are your key strengths? 

  • A passion of working with data
  • Enterpreneur spirit
  • Open minded; willing to learn and look for alternative solutions
  • Dynamic and hard working

 

Your degree:

You have finished your Master’s degree or PhD in Mathematics, Applied Science, Computer Science, Statistic, Physics, Econometrics, Actuary, or comparable field.

Your experience

0-2 years’ experience in the field:

  • Our ideal candidate is passionate about working with data, professionally or in leisure time.
  • SQL, OLAP, JSON, XML have no more secrets for you. 
  • You are able to manage and analyse large data sets with analytic rigor by using statistical methods such as Exploratory data analysis, Bayesian statistics, Probability Theory, Regression, Correlation, Monte Carlo, hypothesis testing. 
  • You are familiar with programs like Python/R/SPSS, Web scraping, Java, .NET, C#. 
  • Previous experience or proven interest in machine learning, data/text mining, data ingestion, supervised/unsupervised learning predictive algorithms, classifiers, association, regression, Trees, KNN are a plus.
  • Ideally, you will possess a wide range of technical skills and highly proficient in turning data discoveries into insights for the business. 
  • Knowledge in the field of financial services, marketing or client behavior is an advantage (banking industry, telecom)

 

Your profile

  • A great drive and You challenge your colleagues and yourself.
  • Constant learning and adapting to a fast-paced environment. Where persistence, innovation, natural curiosity, pragmatic and creativity for problem solving are the key words.
  • You have excellent communication skills, can clearly present and visualize your work to others. You can clearly communicate the outcomes of complicated analyses. Making complex things simple without dropping the essence of the problem.
  • This unique combination makes you a good team player, but you are also able to work independently on different cases.

What can we offer you? 

You can count on KBC for:

  •  active support during your career,
  • an exceptional range of training and development opportunities,
  • many different career opportunities,
  • a permanent contract,
  • a competitive salary package, including an extensive package of additional benefits and special terms for employees for our banking and insurance products,
  • possibilities to integrate your work and private life,
  • a dynamic working environment with an open culture and pleasant atmosphere.

 

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 .

Send your job application today! 

Apply by following this link.

Job – ULB – Postdoc in Machine Learning – 2 years

ULB

ULB MLG Brussels: Postdoc in machine learning, data science and big data for security (e.g. fraud detection)

2 year postdoc position

Description

Research in big data and scalable machine learning with application to security problems (e.g. fraud detection) in the context of a project funded by Brussels Region.

http://mlg.ulb.ac.be/BruFence

Required skills:

  • you have a PhD in Machine Learning, Computational Science, (Bio)Engineering, Data Science, or equivalent.
  • Expertise in statistical machine learning, data mining, big data, map reduce, Spark, python, R programming.
  • Plus: expertise in application of big data mining to real problems, security applications, notably credit card fraud detection
  • You are fluent in English.
  • The successful applicant will be hosted by the Machine Learning Group, co-headed by Prof. Gianluca Bontempi.

    Starting date: asap
    For more information please contact Pr. Gianluca Bontempi, mail: gbonte@ulb.ac.be.
    Please send your CV, motivation letter and contact information for three references, publication list with indication of the citation number of each published paper.

Nr of positions available : 1

Research Fields

Computer science – Modelling tools

Career Stage

Experienced researcher or 4-10 yrs (Post-Doc)

Research Profiles

First Stage Researcher (R1)

Comment/web site for additional job details

mlg.ulb.ac.be