Scientific Software Engineer
£500 per day
Local Government
Contract/Interim
South West
Exeter
VR/44642/DC
06-11-2024 03:02 PM
Interim Senior Scientific Software Engineer
Location: Exeter / Hybrid
Pay Rate: £500 per day (umbrella)
About the Role:
A public sector body is seeking an Interim Senior Scientific Software Engineer to join a cross-organisational team working on an AI-driven project. The primary responsibility of this role is to provide technical leadership and coordination across a team of Scientific Software Engineers and Data Scientists, acting as Scrum Master to support effective agile delivery. This position focuses on enhancing the team's technical leadership and agile practices, complementing the existing scientific leadership.
Key Responsibilities:
Location: Exeter / Hybrid
Pay Rate: £500 per day (umbrella)
About the Role:
A public sector body is seeking an Interim Senior Scientific Software Engineer to join a cross-organisational team working on an AI-driven project. The primary responsibility of this role is to provide technical leadership and coordination across a team of Scientific Software Engineers and Data Scientists, acting as Scrum Master to support effective agile delivery. This position focuses on enhancing the team's technical leadership and agile practices, complementing the existing scientific leadership.
Key Responsibilities:
- Provide technical leadership to deliver project milestones in collaboration with the project manager and team members.
- Act as Scrum Master, facilitating agile ceremonies and supporting the team to achieve optimal workflow.
- Lead the development of technical plans and roadmaps for the FastNet capability.
- Collaborate closely with the project manager to ensure effective agile delivery practices are in place.
- Expert knowledge of Python and experience with quality assurance practices, including testing and documentation.
- Proficient in agile development practices, particularly with the Scrum framework.
- Knowledge of machine learning workflow development and deployment on cloud platforms such as AzureML.
- Familiarity with handling large structured and unstructured datasets, ideally with geospatial data.
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