We are seeking an enthusiastic and proactive Senior Data Science Specialist to join our dynamic technical operations team, which strives to provide a sector leading technical support for FSE and the wider University. With a commitment to customer service excellence and a passion for science and engineering, the Senior Data Science Specialist will provide an agile technical support service to staff and students to support teaching, research and professional services. FSE’s research and teaching quality is recognised globally; this is an exciting opportunity to join us in Manchester and contribute to the provision of a sector leading technical service.

The overall role of the job is to develop required advanced time-series modelling and prediction algorithms or software for SF6 leakage analysis in a project funded through the UKRI Strategic Innovation Fund. In-depth knowledge, experience and programming skills are fundamental in time series models such as ARIMA and machine learning models such as recurrent networks, convolutional neural networks, LSTM and autoencoders. Along with leakage monitoring and modelling, maintenance scheduling is also important part of the work. Experiences in optimisation and scheduling are also essential, along with programming, time management and inter personal skills.

• Setting up required data science (DS) machine learning (ML) platform and libraries (e.g. Statsmodels, Scikit Learn, Pytorch, Tensorflow).
• Data resources and collections (e.g. collecting monitoring and leakage data from collaborators) and data curation and management.
• Designing and building robust time series models and analysis (developing suitable time series models for SF6 leakage data and predictive maintenance for particular sites and networks).
• Testing the developed models at various sites and integration for operational tests and validations.
• Reporting to and interacting or liaising with the University of Manchester team and the entire programme team for project needs.

As this role involves research at a postgraduate level, applicants who are not an EEA national or a national of an exempt country and who will require sponsorship under the Skilled Worker route of the UK Visas and Immigration’s (UKVI) Points Based System in order to take up the role, will be required to apply for an Academic Technology Approval Scheme (ATAS) Certificate and will need to obtain this prior to making any official visa application UKVI)

• Setting up required data science (DS) machine learning (ML) platform and libraries (e.g. Statsmodels, Scikit Learn, Pytorch, Tensorflow).
• Data resources and collections (e.g. collecting monitoring and leakage data from collaborators) and data curation and management.
• Designing and building robust time series models and analysis (developing suitable time series models for SF6 leakage data and predictive maintenance for particular sites and networks).
• Testing the developed models at various sites and integration for operational tests and validations.
• Reporting to and interacting or liaising with the University of Manchester team and the entire programme team for project needs