The Research Fellow in Data Science will be expected to support a variety of academic projects in social data science, especially in liaising between academic researchers and LSE’s new High Performance Computing (HPC) and private cloud computing services. The post is based in SEDS, but will involve working with researchers across the School, cooperating closely with the HPC and Information Management Technology division, and frequently collaborating with SEDS partners at the Data Science Institute at Imperial College London.
The Fellow will have extensive computing and applied data science skills with a social emphasis, including such topics as: social media data, text analysis, network analysis, financial data including real-time streaming data, and experimental or quasi-experimental data on large groups. The Fellow will also have a wide range of computing skills including database management, programming, working with code repositories (such as GitHub) UNIX and cloud computing experience, working with unstructured text data, and publishing materials on the web using content management or similar systems. A desire to encounter and resolve new research-oriented computing problems with a creative and people-oriented approach is essential to this role. The role also involves training others in applied data science techniques, such as contributing to teaching in data science (depending on demand and the candidate’s background), leading workshops, and generally collaborating with a broad base of social scientists and data scientists at LSE and with its external partners.
The successful candidate will have initiative and ambition and be expected to actively participate in building bridges and networks within the School and externally with other researchers and private stake-holders. A typical candidate profile will be a postgraduate (by the post start date) in data science or a cognate social science field with extensive computing experience, who wishes to gain experience working in a prestigious, exciting, and entrepreneurial environment that offers significant possibilities for networking and advancement.
We offer an occupational pension scheme, generous annual leave and excellent training and development opportunities.
For further information about the post, please see the how to apply document, job description and the person specification linked to in the advert on the LSE website
Interviews are likely to take place on Wednesday 17 January 2018 in person or via Skype.
If you have any technical queries with applying on the online system, please use the “contact us” links at the bottom of the LSE Jobs page. Should you have any queries about the role, please email K.R.Benoit@lse.ac.uk.
The closing date for receipt of applications is 1 January 2018 (23.59 UK time). Regrettably, we are unable to accept any late applications.