Senior Geospatial Data Scientist - Data Analytics and Science Hub AI Incubator
| Posting date: | 27 March 2025 |
|---|---|
| Salary: | £41,220 to £49,020 per year |
| Additional salary information: | National £41,220 - £45,400 London £44,500 - £49,020 For details of our pay on appointment policy, please see below under the heading ‘Salary’. |
| Hours: | Full time |
| Closing date: | 07 April 2025 |
| Location: | York |
| Company: | Government Recruitment Service |
| Job type: | Permanent |
| Job reference: | 393354/4 |
Summary
CAID, in partnership with Digital, Data Technology and Services (DDTS) is delivering the DASH programme to transform data science and analysis across the Defra group by delivering scalable, adaptable, future-ready and user-oriented services that nurture a highly skilled community of analysts and scientists.
CAID lead the community, capability and engagement elements and provide the data science expertise both within the programme and to support the analytical and science community. DDTS deliver the data and technology capabilities, primarily through the development and delivery of the DASH Platform, and its ongoing support and maintenance.
In response to the increasing demands and opportunities that evolving AI capabilities are bringing to Defra group and the successful uses of AI such as the AI4Peat project that DASH is already supporting, DASH is establishing a new AI incubator. This team will bolster and enhance the current support offer to data scientists in Defra group, and will expand the department’s capability, applying AI approaches to a wide range of use cases.
As a Senior Geospatial Data Scientist in the DASH’s AI incubator, you will harness the power of geospatial tools to deliver innovative geospatial analyses and support the development of deep learning applications on the DASH platform. You will play a key role in scoping, designing, and delivering small-scale deep learning projects, helping to unlock insights from environmental data and address key policy challenges.
This role is ideal for an experienced user of geospatial tools (e.g., Esri, QSIS) who is passionate about applying geospatial technology to drive impactful environmental outcomes.
The Department for Environment, Food and Rural Affairs (Defra) is the UK government department responsible for safeguarding our natural environment, supporting our world-leading food and farming industry, and sustaining a thriving rural economy. Our broad remit means we play a major role in people's day-to-day life, from the food we eat, and the air we breathe, to the water we drink.
Encouraging diverse applicants
We recognise the challenges that people with (multiple) protected characteristics may experience on the job market and in their career progression. We are fully committed to being an inclusive employer and ensuring equal opportunities. We are keen to make our workforce as diverse as possible, and we hope to attract applications from underrepresented groups.
As a Senior Data Scientist, you will be expected to work on the following.
Geospatial Analysis:
- Conduct detailed geospatial analyses using various geospatial tools such as Esri (e.g., ArcGIS Pro, ArcGIS Online) and QGIS.
- Create high-quality maps, reports, and visualizations to support evidence-based decision-making.
- Develop workflows for spatial data integration, processing, and analysis, ensuring accuracy and efficiency.
Deep Learning with Geospatial Tools:
- Utilize deep learning tools to scope and execute small-scale projects for tasks such as feature extraction, object detection, and change detection.
- Experiment with and fine-tune pretrained deep learning models directly.
- Collaborate with stakeholders to design workflows for applying deep learning techniques to specific environmental challenges, such as monitoring land use changes or identifying ecological features.
Project Support and Guidance:
- Act as a go-to expert for data science teams across Defra, offering guidance on geospatial tools and workflows.
- Support teams in exploring the potential of using geospatial tools for deep learning and other advanced geospatial applications.
- Deliver training sessions to build internal capacity for using geospatial advanced features.
Collaboration and Communication:
- Work closely with policy makers, scientists, and data analysts to understand project requirements and translate them into geospatial solutions.
- Communicate technical findings and recommendations in an accessible manner, emphasising actionable insights.
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