Job – Junior Data Scientist

Screenshot 2016-07-01 12.02.02

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

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 →

Job – Sentiance – Marketing Data Scientist – Antwerp

sentiance_logo_72dpi

Hi Philippe,

Given the topic of the meetup next Thursday, I think the following job opportunity might be relevant to post on your blog 🙂
At Sentiance we’re looking for a data scientist with experience in market segmentation:
http://www.sentiance.com/team/marketing-data-scientist/
However, we always welcome applications of junior candidates too!
http://www.sentiance.com/team/junior-data-scientist/

Thanks, and hope to see you thursday!
Vincent Spruyt
twitter id: @sentiance

As an experienced data analyst, you are ready to kick-off a new adventure in a fast-paced environment where you can work with the latest machine learning technologies and data science tools.

Job description

  1. You will be part of our Data Science Team and you are passionate about machine learning and data analysis.
  2. Using advanced data analytics, you will form hypotheses and draw meaningful insights about user behavior and user segmentation. As a marketing data scientist, you will explore relations between users and their preferences, discover interesting segments, perform advanced clustering and dimensionality reduction techniques.
  3. You will carry out research that will improve our general understanding of our users, and communicate your findings to other team members in order to initiate new platform development cycles.
  4. You will apply your statistical and mathematical background to real-life big-data problems, and use your machine learning knowledge on a day to day basis.
  5. You will work closely & interact with our Data Engineering Team as your work is used to improve our models and is pushed through our release process.
  6. Your main objectives will be the design and implementation of data mining and analysis algorithms and the communication of reports and quality metrics for current production processes.

Desired Skills & Experience:

  1. You have a masters degree or PhD in computer science or related field.
  2. You are an expert in advanced analytics and are experienced in hypothesis testing.
  3. You possess a deep understanding of clustering, manifold learning and predictive modeling techniques.
  4. You have good knowledge of and experience with any of Python, Matlab or R.
  5. You have a strong mathematical background and analytical mindset.
  6. You are fluent in English. Dutch is a plus.
  7. You can work independently and take matters into your own hands.
  8. The ability to quickly learn new technologies and successfully implement them is essential.

Bonus

Experience with any of the following is considered a plus:

  • Advanced Python knowledge and experience
  • Scikit-learn, Pandas, Numpy, Matplotlib
  • Experience with Spark or the Hadoop eco-system
  • Machine learning, data mining, data visualization

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! 

Please send Sentiance your resume and a strong motivation with reference sentiance/2015/MDS or apply on LinkedIn.

Challenge – Online – Integra Gold Rush

IntegraGoldRush

Who wants to be part of our Team of Belgian gold diggers? ( please add a comment if interested)

I just received this exciting message from Canada. Should we put a team together, seems to be the perfect for real miners, no ?

Hello Philippe,

 
We are excited to launch the Integra Gold Rush Challenge this September – one of the largest ever mining industry incentive prize competitions to hunt down the next big gold discovery in Val-d’Or, Canada.

Opened in 1935, the Lamaque mine remained in operation for 50 years, processing more than 24 million tons of ore and 4.5 million ounces of gold. The Lamaque mine remained untouched and relatively forgotten for nearly 30 years, until Integra Gold purchased it in October, 2014.

Along with the purchase came 6 terabytes of information, spanning 75 years of mining history. This database is being turned to the public to help unlock its value through innovative and comprehensive solutions.

The Integra Gold Rush Challenge invites people from around the world, from any background to analyze this data and win prizes totaling CAD $1 million.

You may visit the challenge page to find out more and to register as an innovator. 

Please let me know if you would like to participate or know anyone else who might be interested in participating.

Thanks
Henna.

———-

Join our next meetup on Sept 24th @VUB:

How Data Science is Transforming Sales and Marketing

Thursday, Sep 24, 2015, 6:30 PM

VUB – Aula QD
Pleinlaan 2B – 1050, Brussels Brussels, BE

149 Business & Data Science pro’s Attending

Agenda:18:30 monthly update by Philippe Van Impe• Official opening of the HUB with Alexander De Croo on 20/10• How to benefit from the training facilities from ‘European Data Innovation Hub’ – here is the overview of the trainings organized.• how to benefit from the DataScience co-working space• nice list of outstanding job opportunities19:00…

Check out this Meetup →

Treat yourself to some #datascience education:

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.

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

Registrations for Data Science and Big Data training programmes are now open.

The European Data Innovation Hub organizes with its partners a full serie of Data Science and Big Data training programmes.

You can expect

  • a series of executive training to support your management in understanding the benefits of analytics
  • a series of coached MOOCs on machine learning and big data technology
  • a series of hands-on training on the different datascience technologies

All members of the European Data Science and Big Data communities are welcome to use our Brussels based professional facilities to give their training. The members of the hub will promote your training and include it on our e-learning platform for further use.

Here is an overview of the trainings that we have already scheduled for the coming months:

Data Innovation Training Hub

Brussels, BE
486 Fast learners

This group is an initiative from the nonprofit European Data Innovation Hub, the premier networking space where business, startup, academic and political decision makers share…

Next Meetup

Hacking opendata with Neo4j

Thursday, Feb 18, 2016, 6:00 PM
1 Attending

Check out this Meetup Group →

Interviews with Data Scientists – The collection – Peadar Coyle

Excellent set of interviews with Data Science professionals by Peadar Coyle.

Models are illuminating and wrong

In the last year or so I’ve put together a collection of interviews with Data Scientists.

Here is a list of them

  • Thomas Levi – Plenty of Fish an Online Dating Website
  • James Long – A data artisan with experience in Re-insurance
  • Radim Rehurek – A data science and engineering consultant famous for the Gensim Topic Modelling library
  • Ignacio Elola – The data guru at Import.io a platform for enabling easy access to web data.
  • Eddie Bell – Lead Data Scientist at Lyst – a Fashion recommendation website

View original post

Job – B&D – Analytics and Data mining Consultant – Brussels

logo_businessdecision

Function

You will be assisting in the co-ordination and implementation of financial crime consulting offering by:

  • providing project support
  • drafting business requirements and delivering analytical data mining assignments and statistical models to monitor and review the data mining and analytics conducted for patterns and anomalies indicating possible tax fraud
  • to facilitate effective follow-up to identified issues, ensure completeness of analytics follow-up and to promote enhanced methods/processes in system-wide data analysis, including recommending additional ongoing and ad-hoc queries, in relation to fraud detection

Among principal assignments, the successful candidate will:

  • Perform business analysis to support the deployment of fraud prevention analytical models
  • Lead/Perform data and quality analysis including data mapping reviews, data validation and remediation, alert validation and issue impact analysis
  • Communicate with clients to assess solution fit and identify product gaps
  • Perform statistical analysis and tune our growing model set
  • Respond to Business and Functional requirement requests

Profile

  • Knowledge of data mining and analytics including statistical and predictive analysis, quantitative and qualitative data analysis methodologies
  • Research and investigation methodologies, and ability to utilize queries and tools and analyze data sets from large, complex and disparate systems, in order to research and analyze a broad range of data
  • Knowledge of fraud and of methodologies and best practices in the detection/control of fraud including fraud techniques/practices, fraud concealment, tax fraud criminal offenses, anti-fraud techniques, fraud investigation:
  • Certified SAS professional with a strong background in the use of analytical tools and statistical software, especially SAS Enterprise Miner
  • Oral and written communication skills, to liaise and consult with various parties to gather and assess data and to prepare reports and proposals with a minim of French and Dutch or which ideally both if not one fluent in writing and speaking.

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 .

Job – Sogeti – Business Intelligence Analyst

 logo_sogeti

Tasks:

  • Gathering business requirements
  • Development of data mining solutions
  • ETL processes
  • Data modelling
  • Design and development of reporting applications
  • Physical DB design

Knowledge and skills :

  • In-depth knowledge of data warehouse design & architecture

  • In-depth knowledge of Business Objects

  • In-depth knowledge of relational database systems applied to data warehouse
  • In depth knowledge of SQL
  • In depth knowledge of business intelligence reporting tools
  • Good knowledge of ETL tools
  • Good knowledge of modelling tools
  • Good knowledge of online analytical data processing (OLAP) and data mining tools
  • Ability to understand, speak and write French and English

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 .
Candidates can also post their availability here.

Here is the original  jobpost .

Apply:  APPLY NOW

 

Job – NG DATA – Big Data Scientist

NGDATA

Job Description

In the era of Big Data, data is not useful until we identify patterns, apply context and intelligence. The data scientist, as an emerging career path, is at the core of organizational success with Big Data and for humanizing the data to help businesses better understands their consumer.

As a data scientist, you sift through the explosion of data to discover what the data is telling you. You figure out “what questions to ask” so that relevant information hidden in the large volumes and varieties of data can be extracted. The Data Scientist will be responsible for designing and implementing processes and layouts for complex, large-scale data sets used for modeling, data mining, and research purposes.

Opportunities

  • Be a true partner in defining the solutions, have and develop business acumen and bring technical perspective in furthering the product and business;
  • Aggregate data from various sources;
  • Help define, design, and build projects that leverage our data;
  • Develop computational algorithms and statistical methods that find patterns and relationships in large volumes of data;
  • Determine and implement mechanisms to improve our data quality;
  • Deliver clear, well-communicated and complete design documents;
  • Ability to work in a team as well as independently and deliver on aggressive goals;
  • Exhibit Creativity and resourcefulness at problem solving while collaborating and working effectively with best in class designers, engineers of different technical backgrounds, architects and product managers.

Personal Skills

  • You have a logical approach to the solution of problems and good conceptual ability and skills in analysis;
  • You have the ability to integrate research and best practices into problem avoidance and continuous improvement
  • You possess good interpersonal skills;
  • You are self reliant and capable of both independent work and as member of a team;
  • You are persistent, accurate, imaginative;
  • You are able and have the discipline to document and record results;
  • Be customer service oriented;
  • Be open minded and solution oriented;
  • You enjoy constantly expanding your knowledge base;
  • You are willing to travel up to five days per month.

Technical Background

The successful candidate should have 5+ years experience in large-scale software development, with at least 3 years in Hadoop. Have a strong cross-functional technical background, excellent written/oral communication skills, and a willingness and capacity to expand their leadership and technical skills.

  • BS / MS in computer Science;
  • Strong understanding of data mining and machine learning algorithms, data structures and related core software engineering concepts;
  • Understanding the concepts of Hadoop, HBase and other big data technologies; Understanding of marketing processes in the financial and or retail market;
  • Have a sound knowledge of SPSS and SQL

Apply:

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

Here is the original jobpost .

Apply:  Upload your resume or send it to jobs@ngdata.com. We look forward to your application!