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.
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.
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.
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.
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.
You will be part of our Data Science Team and you are passionate about machine learning and data analysis.
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.
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.
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.
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.
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:
You have a masters degree or PhD in computer science or related field.
You are an expert in advanced analytics and are experienced in hypothesis testing.
You possess a deep understanding of clustering, manifold learning and predictive modeling techniques.
You have good knowledge of and experience with any of Python, Matlab or R.
You have a strong mathematical background and analytical mindset.
You are fluent in English. Dutch is a plus.
You can work independently and take matters into your own hands.
The ability to quickly learn new technologies and successfully implement them is essential.
Experience with any of the following is considered a plus:
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 ?
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.
Join our next meetup on Sept 24th @VUB:
How Data Science is Transforming Sales and Marketing
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…
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: email@example.com.
Please send your CV, motivation letter and contact information for three references, publication list with indication of the citation number of each published paper.
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 486Fast 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…
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
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.
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
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 firstname.lastname@example.org . Candidates can also post their availability here.
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.
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.
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.
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;