New competition challenges scientists to produce accurate forecast of 2020 UK energy demand – by October 2014

SAS science competition logo

SAS, a business analytics software and services provider, has launched a six month long competition aimed at encouraging data scientists to produce the most accurate forecast – by October 2014 – of UK energy demand in 2020.

Open to undergraduates, postgraduates and business professionals, the competition – which is now open – aims to produce an innovative forecast of energy demand, using open data from the UK government to forecast the number of terawatt hours of electricity likely to be consumed in the UK by 2020.  

The judges are looking for written submissions and a video presentation; the more interesting and more visual the better.

Laurie Miles, Head of Analytics at SAS UK & Ireland, who will be part of the judging panel, said: “We are looking for data scientists with great ideas and projections, to show us the impact data can have on infrastructure, power usage and the growing use of devices”.

Former cabinet minister Dr. Liam Fox, MP, is also a member of the Top Data Scientist judging panel. He commented: “Understanding data trends will provide the UK with unrivalled opportunities to address some of the most critical issues facing our society, whether that’s the economy, supporting an ageing population or how to tackle the energy crisis.

“The UK is currently faced with a dearth of critical data skills and we need more individuals with the skills to drive this change and create new opportunities. This competition is important not only to identify key talent within data science but also to force the debate around vital areas like the future of energy.”

 Other members of the judging panel include; –

  • Dr Carsten Sørensen, Associate Professor of Information Systems and Innovation, London School of Economics
  • Kenneth Cukier, Data Editor, The Economist, and
  • Hannah Redler, Head of Space and Arts Programme, the Science Museum, London.

The competition is now open for entries, which must be submitted by 7 October, 2014. 

For more information:

http://sas.com/uk/datascientist

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