Job – Skyline- Data Analytics professional

skyline

just received this email,

Name: Veerle Ledoux
Email: Veerle.Ledoux@skyline.be

Dear Philippe

At Skyline Communications, we currently have a job opening for a researcher in data science and big data analytics. It would be great if our job offer could be posted on your blog.

Skyline Communications is widely recognized as the global leading supplier of end-to-end multivendor
network management solutions, and systems have been deployed by leading operators in the HFC broadband, satellite, IPTV, broadcast, mobile and IT industry on all continents. The company is renowned for its technological leadership, and is dedicated to continuous R&D efforts, redefining
how operators can manage their ever more complex platforms in a more efficient way.

The flagship DataMiner network management platform collects a tremendous amount of data by measuring a vast spectrum of heterogeneous parameters in the network. Within this real-time streaming data lies an immense amount of information waiting to be explored. Currently, Skyline Communications is looking for someone to strengthen Skyline’s data analytics team. The job posting is available at this link:
http://skyline.be/skyline/jobs/telecom-network-management-researcher

Many thanks for your consideration

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 .

Interested? The job posting is available at this link:
http://skyline.be/skyline/jobs/telecom-network-management-researcher

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.

Check out the full agenda here.

Video channel and e-learning:

Follow the link to subscribe to our video channel.

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
1,452 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

Using Open data to promote Data Innovation

Thursday, Nov 26, 2015, 6:30 PM
88 Attending

Check out this Meetup Group →

Information and Networking Day on H2020 ICT-15 Big Data PPP Lighthouse Projects

COM LOGO NEW(1)

The aim of the event is to inform and guide potential proposers preparing project proposals, to facilitate sharing of ideas and experiences. It will give participants the chance to network and to find partners for their projects.
Date: 01/12/2015
Venue: Albert Borschette Congress Center in Brussels
Organiser: European Commission, Data Value Chain Unit

A special Information and Networking Day dedicated to H2020’s ICT-15 ‘Big Data PPP: Large Scale Pilot actions in sectors best benefitting from data-driven innovation’ (also known as Lighthouse Projects) will be organised by DG Connect – Data Value Chain Unit, on 1st December 2015 in Albert Borschette Congress Center in Brussels.

Programme

Lighthouse projects are large scale Innovation Actions aiming to practically demonstrate how big data technologies can be transformative for data intensive industrial domains. Lighthouse projects are expected to deliver commercial and technological impact. Possible industrial domains of applications include (but are not limited to) health, energy, environment, earth observation, geospatial, transport, manufacturing, finance, media.

The current outline of the draft agenda can be found HERE.

Registration

The registration to the event is now open. Click HERE to register. The closing dateis 24th November 2015 but the online registration may be closed earlier if the event is fully booked.

After the confirmed registration you will have the possibility to upload a presentation for the networking and partner finding sessions (max 3 slides for 3 minutes presentation).

Please note that bilateral meetings with EC Project Officers to discuss proposal ideas (proposal clinics) will *not* be possible, in compliance with H2020 rules.

Terms of participation

There is no participation fee but the online registration and confirmation e-mail are mandatory. Due to limited number of places participation will be possible only upon a confirmed online registration. Please do not make travel arrangements before you receive a confirmation email.

There will be no possibility to register on site. Do not forget to print your confirmation and bring it with you. Travel, accommodation expenses as well as meal must be borne by the participants and will not be reimbursed by the European Commission.

Additional information

• Background Notes H2020-ICT-15-2016
• Horizon 2020 – The work Programme 2016-2017 Information and Communication Technologies
• ICT Research & Innovation under Horizon 2020
• Another Info Day on ICT 14, ICT 15, ICT 16 and ICT 17 will be organised in January 2016, more information on the dedicated event website
• H2020 Reference documents

Free Hands-on Training – Workshop – Elastic Search on Open Data – Dec 2nd at 18:30

hands-on logo-elastic

Here is the training on Elastic that Fabien promissed us. In order to make it real we decided to do a hands-on workshop using Open datasets made in Belgium. The number of participants will be limited to 25.

What:

Hands-on Workshop

Using open Belgian data-sets, elastic search and kibana to create dashboards and analytic views.

Target audience:

Everyone with a computer 🙂 .

No real coding during the exercise.

No downloads, just using web interfaces.

Practicalities:

  • When: Wednesday December 2nd 2015 at 18:30
  • Where: European Data Innovation Hub, Vorstlaan 23 in Brussels
  • Registration: please use eventbrite to register and to collect your ticket.
  • Duration: 2.5 hours starting at 18:30 sharp.

Motivation

Learn how to exploit open data set with Elastic search and Kibana.

Overview:

We will download several json datasets from open data (http://data.gov.be/)

Feed elastic with logstash.

Create amazing dashboard with kibana.

Execute complex query (Full text / geo aggregation)

Topics

  • Found Usage.
  • LogstashLoad data in Elastic
  • Elastic search: Search and analyze data in real time. Learn about filters and queries in an inverted index, relevance score calculations, and more.
  • KibanaSee the Value in Your Data
    • Flexible analytics and visualization platform
    • Real-time summary and charting of streaming data
    • Intuitive interface for a variety of users
    • Instant sharing and embedding of dashboards

Prerequisite:

Each participants must be a member of the Brussels Data Science Community. join here

The participant must have his PC/Mac/Linux machine.

You need to register upfront to “Found” , the Elastic cloud environment.

https://www.elastic.co/found/signup    Free trial 14 days

About the trainer:

logo-elastic

Job – Artycs – SENIOR DATA SCIENTIST – Brussels

Artycs

The team of Artycs are active members of the Brussels Data Science Community and their offices are located in the European Data Innovation HUB, an incubator focused on data related startups.

ARTYCS is a start-up providing advisory services on Big Data strategy, full end-to-end management and delivery of data analytics projects and sourcing of data science related profiles. 

ARTYCS stands for “The Art of Analytics”. This represents our main values i.e. state of the art analytics skills combined with creativity and innovation in a client oriented mindset. 

At ARTYCS, we invest in Research & Development to work with the latest methods and technologies.

Being part of ARTYCS is the will to progress, to be an entrepreneur and to grow as an individual and as a company.

Becoming an employee at ARTYCS means working in a dynamic environment where there is room for new ideas and entrepreneurship.

At ARTYCS, we know that being a Data Scientist requires an extended set of key skills. We know also that Data Science is a dynamic field. For this reason, we are committed in developing our staff through an active Data Science Development Program. Concretely, this means that during your career at ARTYCS, you will be provided with a development plan that will clearly state the list of trainings you will follow and their timing, the development points for which you will receive coaching from our senior management on a regular basis, the data science events you will attend. With this program, we aim not only at developing our Data Scientists but also at ensuring that they are at the forefront of Data Science.

For one of our clients, a key player in financial services based in Brussels, we are looking for a Data Scientist. This is an exciting and challenging position as the candidate will join a dynamic, successful and rapidly growing team responsible for handling a large variety of Big Data business use cases. The candidate will be key in delivering the business use cases and expanding the reach of the team.

In this context ARTYCS is looking for a Senior Data Scientist to integrate our DS team, to take part to studies at clients and to be an active resource in the growth of the company:

Job description

Skills

  • Ability to learn quickly, adjust to changes and think outside the box
  • Creativity, curiosity and no non-sense approach
  • Positive attitude, self-motivated and confident
  • Excellent time management and organizational skills with attention to detail
  • Experience working with customers to identify and clarify requirements and ways to meet needs
  • Strong verbal and written communication skills, good customer relationship skills
  • Stay abreast of new tools and technologies to practice up-to-date data analytics strategies

Qualifications

  • Master’s degree in statistics, applied mathematics, or a related quantitative field
  • Strong experience with high-level programming languages such Python & R
  • Knowledge on Java and Scala is an asset
  • Work experience using applied machine learning or statistical modelling; knowledge of algorithms spanning clustering, regression, classification, mixture models, etc…
  • Experience with command line tools, relational databases (i.e. SQL), data visualization (Shiny, and version control (i.e. git)
  • Broad based understanding of the Hadoop ecosystem
  • Experience with Open Source big data technologies like Spark, Pig, Hive, HBase, Kafka, Storm
  • Knowledge of data extraction and ETL is a must
  • Knowledge of financial sector is a plus

Description of the position

  • Job Title: Senior Data Scientist
  • Location: Brussels, Belgium

For this position, we offer an attractive salary package including benefits (e.g. lunch vouchers, phone, company car, etc) and a variable part, depending on the seniority of the candidate. 

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 .

Interested? Contact Laurent Fayet (0476/79.46.28),  laurent.fayet@artycs.euhttp://www.artycs.eu

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.

Check out the full agenda here.

Video channel and e-learning:

Follow the link to subscribe to our video channel.

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
1,451 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

Using Open data to promote Data Innovation

Thursday, Nov 26, 2015, 6:30 PM
86 Attending

Check out this Meetup Group →

Training – Hands-on with R Shiny – November 26th

screen-shot-2014-09-18-at-10-09-14-pm

Shiny lets you create nice reactive web applications on top of R computations without any web development skills required. In this two-days Shiny course you will create your own sophisticated application and learn how to deploy it.

We start off easy by learning how to control the layout of your application and how to add widgets. Next up we will learn about reactivity. What options does your application have to react on user input: immediately or via submit buttons. During the course, applications will get more sophisticated by adding entire R scripts and input data. You will also learn how to return results to your users: displaying results, downloading pdf’s or other file formats, mailing results, … Moreover we will go into detail on how to interact with the results. For example via hovering over or clicking on plots.

At the end you will learn how to deploy your web application on shinyapps.io as well as on your own server.

logoThis training event is organised in collaboration with Oak3 (www.oak3.be). The Oak3 Academy is an IT Learning Center providing hands-on, intensive training and coaching to help students develop the skills they need for a successful career as an Information Technology Professional or as a knowledge worker (end-user of software). Our goal is to provide the highest quality training and knowledge transfer that enables a person to start or enhance his or her career as an IT professional or knowledge worker, in a short period of time. We therefore offer knowledge assimilation, facilitate expertise transfer and provide a rewarding learning experience. Our training solutions are designed to help students learn faster, master the latest information technologies and perform smarter.

Prerequisites: Previous experience with R is required, no HTML or CSS knowledge is needed.

When: Thursday, 26 November 2015 at 9:00 AM Friday, 27 November 2015 at 5:00 PM (CET)

Where: European Data Innovation Hub – 23 Vorstlaan Watermaal-Bosvoorde, Brussel 1170

Registration: Eventbrite

Training – Hands-on with SparkR – Brussels – November 24

sparkr_custom_logo

As of June 2015 SparkR is integrated in Spark-1.4.0. However this is still work in progress: in the original version, no Spark MLlib machine learning algorithms were accessible via R. In Spark-1.5.0 it is already possible to create generalized linear models (glm).

In this one-day SparkR course, you will understand how Spark is working under the hood (MapReduce paradigm, lazy evaluation, …) and learn how to use SparkR. You will start setting up a local Spark cluster and access it via R. Next up you will learn basic data transformations in SparkR, either via R code or via SparkSql. Finally we will use SparkR’s glm and compare it to R’s glm and we will implement our own machine learning algorithm.

logoThis training event is organise in collaboration with Oak3 (http://www.oak3.be). The Oak3 Academy is an IT Learning Center providing hands-on, intensive training and coaching to help students develop the skills they need for a successful career as an Information Technology Professional or as a knowledge worker (end-user of software). Our goal is to provide the highest quality training and knowledge transfer that enables a person to start or enhance his or her career as an IT professional or knowledge worker, in a short period of time. We therefore offer knowledge assimilation, facilitate expertise transfer and provide a rewarding learning experience. Our training solutions are designed to help students learn faster, master the latest information technologies and perform smarter.

Prerequisites: Previous experience with R is required, notions of Apache Spark are useful but not required.

When: Tuesday, November 24, 2015 from 9:00 AM to 5:00 PM (CET)

Where: European Data Innovation Hub – 23 Vorstlaan Watermaal-Bosvoorde, Brussel 1170 BE

Registration: Eventbrite

Training – Hands-on – Spark Streaming – Brussels – December 1st

spark-streaming-logo_0

In this one-day Spark Streaming course you will learn setting up your very own Spark Streaming applications, and do real-time data processing and analytics. You will start with setting up the data ingestion from HDFS, Kafka, and even Twitter.

Next up you will learn about the benefits from using one integrated framework for both batch and streaming processing. You will combine streaming and historical data, in order to create valuable applications.

You will learn how fault-tolerance is built into Spark Streaming, and might even get a hint of how to combine it with the Spark MLlib machine learning library.

This training evelogont is organised in collaboraton with Oak3 (http://www.oak3.be). The Oak3 Academy is an IT Learning Center providing hands-on, intensive training and coaching to help students develop the skills they need for a successful career as an Information Technology Professional or as a knowledge worker (end-user of software). Our goal is to provide the highest quality training and knowledge transfer that enables a person to start or enhance his or her career as an IT professional or knowledge worker, in a short period of time. We therefore offer knowledge assimilation, facilitate expertise transfer and provide a rewarding learning experience. Our training solutions are designed to help students learn faster, master the latest information technologies and perform smarter.

Prerequisites: Previous experience with programming for Apache Spark in Scala is required.

When: 1 December 2015 from 9:00 AM to 5:00 PM (CET)

Where: European Data Innovation Hub – 23 Vorstlaan Watermaal-Bosvoorde, Brussel 1170
BE

Registration: through Eventbrite

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.

Meetup – OCT22 – Brussels – A journey through advanced analytics in insurance

annoucement

Data science is going to drastically change the insurance industry. Through the analysis and exploitation of massive data, the possibilities opened up by Big Data will have a long-term impact on the market. Data science will allow insurance companies to offer better services individually adjusted to the uses and needs of its beneficiaries.

Agenda:

18:30 monthly update by Philippe Van Impe

19:00  « Geographical pricing in Motor Insurance »
by Xavier Maréchal from Reacfin.

19:25 « A journey through advanced analytics in insurance »
by Colin Molter from AXA

19:50 « Data-drive valuation as an alternative for a grid @ fire insurance  »
by Michaël Peeters from Mimec

20:15 « Overview of the activities of the Fintech community »
by Eric Rodriguez &  Toon Vanagt

20:40 « series of open 5 minutes presentation from anyone with an opinion or interesting project »

  • Noisy Channels by Filip Deryckere
  • Brainvolve by Steven De Blieck
  • transformy.io by Tomas Broodcoorens

21:10 Netorking at the Opinio

Register for free:

The Value of Advanced Analytics in the Insurance business

Thursday, Oct 22, 2015, 6:30 PM

D.0.07
VUB Pleinlaan 2B – 1050 Brussels, BE

123 Business & Data Science pro’s Attending

Data science is going to drastically change the insurance industry. Through the analysis and exploitation of massive data, the possibilities opened up by Big Data will have a long-term impact on the market. Data science will allow insurance companies to offer better services individually adjusted to the uses and needs of its beneficiaries.Agenda:…

Check out this Meetup →

The ABC of Datascience blogs – collaborative update

abc-letters-on-white-sandra-cunningham

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 →