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Data Scientist – StatSports/QUB – Spatio-Temporal Data Analytics

Country/Region : UK - United Kingdom

Website :


This Data Scientist job would involve working across StatSports Group and Queen’s University Belfast (QUB) in a 24-month project funded by Innovate UK. We are seeking to recruit a highly motivated post-doctoral candidate with significant expertise in spatio-temporal data analytics who would be the core contributor in the project. The technical goal of the project is focused on data science methods to discover co-ordinated player movement patterns from the wealth of spatio-temporal player trajectory data that is available within StatSports. As may be obvious, this is a pristine research field with high innovation potential. The player movement database has been gathered by means of the StatSports Apex Pod, which is worn on a daily basis by elite athletes at many of the world’s biggest sports teams (across sports such as soccer and rugby) to monitor their performance.
The successful candidate will deliver technical leadership in developing algorithms for pattern discovery and analysis over spatio-temporal player movement trajectories and commercializing them through StatSports products, and among the core milestones in the project would be to publish the research in top-tier data analytics avenues such as SIGKDD, ICDM, CIKM and ICDE. We expect the successful candidate to have already had experience in publishing at such avenues or similar. The candidate will also have opportunity to co-mentor a PhD candidate at QUB within the same area of data science over spatio-temporal player movement traces; informal/formal co-supervision arrangements could be worked out based on interest alignments.
While the position is based at StatSports, Newry, UK, frequent travel to QUB (40 miles north-east of Newry) is expected and will be facilitated by the project. Newry is located on the Belfast-Dublin highway with easy access to both cities. StatSports expects to develop significant in-house data science research expertise over the next few years, which could lead to opportunities for continued employment beyond the successful completion of the 24-month project. Any queries on the technological scope of the position may be addressed to either the QUB team comprising Dr. Fergal McCaffrey (, Mark Connor ( and Barry Waters ( Queries more appropriate to the QUB side, such as those relating to research focus, may be addressed to Dr. Deepak Padmanabhan (
Candidates in the final stages of the PhD programme are also welcome to apply (the position is expected to start in January 2019).
More details and Application Link:
Closing Date: 10th October, 2018
Expected Start Date: January 2019

Last modified: 2018-10-10 10:10:45