Category: Research | Faculty/Professional Services: Faculty of Science | School/Department: Department of Computer Science | Section: Department of Computer Science | Location: Egham | Post Type: Full Time | Closing Date: 16 Sep 2015 |
This one-year appointment offers a unique and exciting opportunity to drive the adoption of modern principles for predictive analysis and data mining to effect measurable business outcomes with British Gas, an industry-leading energy provider. The appointee will work closely with academic staff at the Department of Computer Science of Royal Holloway as well as with multiple business stakeholders at British Gas to deliver a wide range of new techniques and solutions for achieving measurable business improvements from the interpretation and exploitation of data.
The Department of Computer Science at Royal Holloway carries out outstanding research in the area of Machine Learning and Cloud Computing. Our Computer Learning Research Centre was established in January 1998; it has made major contributions to machine learning research, notably in kernel methods and support-vector machines (for which we developed the first open-source implementation, and published standard textbooks), competitive learning, reinforcement learning, and conformal prediction. We have an excellent publication record in these areas, in which the post holder would be expected to participate. We havealso been involved in industrial applications of machine learning, including medicine and finance.
British Gas, part of the Centrica Group, supplies gas and electricity to UK residential and business customers, provides central heating and gas appliance installation and maintenance, and provides low-carbon and energy efficient products and services. In the last few years, British Gas has been developing a Big Data capability through the creation of a Data Lake and are now looking to exploit it through innovative and creative Data Science projects.
This role will involve a mixture of research, collaboration, promotion and hands-on leadership of projects.As British Gas is establishing new capabilities in Data Science and Big Data in collaboration with Royal Holloway, the appointee will have the opportunity to play a leading role in this process and at the end of the contract may be in a position to apply for a key position as a Data Science Manager at British Gas.
The main responsibilities of the post are: performing research in data science and analytics in collaboration with academics at Royal Holloway; engaging with key stakeholders at British Gas to share knowledge and build understanding at a business level about how data science principles and methods may be exploited to improve business performance; developing a roadmap for Data Science as a capability and sharing this with stakeholders to gain buy-in; delivering viable proof-of-concepts to demonstrate how data science may be used to increase operational performance in areas such as customer experience, business intelligence, and energy forecasting; identifying and analysing feasible new data-oriented applications within British Gas; leading the establishment of a Data Science capability at British Gas; and disseminating results by writing case studies and papers for relevant journals or conferences.
The successful candidate will have been educated at MSc level or equivalent, and have strong data analysis skills as well as knowledge of modern data analysis methods and techniques. Research experience and a record of demonstrable industrial engagement and impact will also be highly valued.
This is a full time post, available from October 2015 or as soon as possible thereafter for a fixed term period of one year. The appointee will work primarily at British Gas facilities in Staines, though regular visits to Royal Holloway in Egham, Surrey for research purposes are anticipated. The two locations are just over two miles apart.
For further details of the Department see our web site http://www.rhul.ac.uk/computerscience or contact the Head of Department at jose.fiadeiro@rhul.ac.uk.