Closing Date: Friday 20th September 2019
Salary: £24,000 - £33,000 per annum. One of the key KTP benefits for graduates is access to a £8,500 training and travel budget over the 24 month project.
Anticipated Interview Date: Wednesday 9th October 2019
Duration: 24 months
About CARD Group Ltd:
Established in 2003, CARD Group is a commercial market research agency specialising in the retail, leisure and foodservice sectors. We work with clients across Europe to conceptualise and develop better ways of providing new consumer insight. Our information is used for everything from planning global store portfolios through to assessing the impact of marketing activities on changing consumer perception.
Find out more by visiting: https://www.card-group.com/
The Role: Data Scientist
Main Activities and Responsibilities:
Knowledge Transfer Partnerships is a UK programme that enables businesses to work with universities to gain access to specialist knowledge and expertise and apply it within their organisation. Each Partnership recruits a Graduate to work in the company, implementing and embedding the latest research techniques. We wish to recruit a highly skilled and motivated graduate to work in CARD Group (based in Belfast) in collaboration with Queen’s University Belfast for 24 months. Through this Knowledge Transfer Partnership, CARD Group seeks to develop an innovative system founded upon statistical principles to qualify the retail, leisure and food service potential of town centres. The system streamlines superior location planning for brands, resulting in sustainable and successful town centres for local authorities.
As a Knowledge Transfer Partnership, the post is for an initial 24 months, with subsequent potential for a longer term role.
You will be working to help realise a new approach for understanding how people choose to visit retail and leisure destinations.
The project will consist of the following key integrated project phases:
- Assessment of current processes and data practices.
- Implementation of statistical tests for rigorous analysis.
- Implementation of Bivariate Discrete Choice Analysis Models.
- Extension to a multinomial discrete choice analysis model.
- Probabilistic Forecasting with Discrete Choice Models
- Visualisation and communication of the data.
The successful candidate must have:
- Hold at least a 2.1 Honours degree (or equivalent) in Statistics, Mathematics, Computer Science or a closely related discipline. Candidates who hold, or are about to obtain a 2.2 in the above in addition to either a relevant higher degree or one year’s relevant experience will also be considered. Please clearly state your qualifications and degree classification when making your application.
- Relevant experience of modelling and solving computer science, mathematics, statistics or engineering problems. (may be demonstrated through a suitable module or project).
- Experience of working with statistical and dynamic programming languages (eg. R, Python or a closely related language).
Informal enquiries may be directed to Karen McGeough.
Telephone: 028 9097 3970