Spatial Data Scientist

at  Centre for Ecology Hydrology

Salary - £37,405 to £39,694
Based in Lancaster, hybrid working options
12-Month Contract
We will review applications upon receipt. We reserve the right to close this advert if we find the right candidate, so we encourage you to apply early.
UKCEH is looking for a Spatial Data Scientist to join our team of talented individuals, contributing to scientific discovery and generating the data, insights and solutions that researchers, businesses and governments need to solve complex environmental challenges.
Working at UKCEH is rewarding. Our science makes a real difference, enabling people and the environment to prosper, and enriching society. We are the custodians of a wealth of environmental data, collected by UKCEH and its predecessors over the course of more than 60 years.

As a valued member of our team, you’ll get:

• 27 days annual leave (prorated for part year working)
• 24 hour, 365-day access to support with physical, mental, social, health or financial issues, plus access to our trained Welfare Officers
• PAYE Pension provided by NEST (via Hays)
• Access to a discount portal

You will carry out work for UKCEH under a contract of services agreement via Hays PLC (Company Number 02150950). You will be paid weekly by Hays PLC by submitting a timesheet to your UKCEH Line manager.
You’ll be joining our Soils and Land Use Science Area to work on the EU-funded project DevelopIng STratEgies by integrating mitigatioN, aDaptation and participation to climate changE Risks (DISTENDER). You’ll be joining a team of enthusiastic researchers exploring the challenge of developing strategies to simultaneously mitigate climate change whilst adapting to its impacts through a co-creative process that works with 5 case studies with a range of real-world challenges across a range of sectors and scales.
You’ll work primarily on a cross-sectoral risk and vulnerability assessment, looking at impacts identified by other sectoral models in the modelling chain in the context of the vulnerability of those exposed to the impacts by considering the available capitals (human, social, financial and manufactured) that are available to draw on to deal with the impacts. This involves developing scenario-specific levels of adaptive and coping capacity developed from appropriate national indicators and overlaying these with risks identified by other sectoral impact models.
You’ll be joining a leading independent, not-for-profit research institute that’s committed to recruiting talented people like you, progressing your career and giving you the support you need to thrive at UKCEH.

Your main responsibilities will include:

• Conducting a cross-sectoral risk and vulnerability assessment, inspired by similar conducted under other projects (e.g., as described in Dunford et al. 2014)
• Working with an interdisciplinary team to adapt the methodology for the assessment based on unique considerations in the DISTENDER project
• Generating scenario-specific coping capacity maps for case studies underpinned by human, social, manufacturing and financial capital indicators and datasets
• Translating climate adaptation and mitigation strategies identified by case studies into quantitative terms for spatial analysis
• Overlaying outputs of other sectoral impact models with coping capacity maps to generate risk & vulnerability maps
• Using R (or Python) to automate analyses to produce outputs
• Interpreting and synthesizing outputs of the assessment for scientific publications

For the role of Spatial Data Scientist, we’re looking for somebody who has:

• A PhD or equivalent experience in environmental science or related topic, with a focus on spatial data analysis
• Experience using R (or Python) for spatial data analysis for the automation of analyses
• Experience translating qualitative information into quantitative representation for modelling
• Knowledge and experience working with large spatial datasets
• Interest in working with both quantitative and qualitative data (Desirable)
• Understanding and/or experience of methods and tools of scenario development (Desirable)
• Proven publication skills (Desirable)

If we’ve just described you, we’d love to meet. Apply now.
Unfortunately, we are unable to offer visa sponsorship for this position at this time.
About Us
Here you can explore the kind of roles we recruit for, search our latest vacancies, learn more about what it’s like to work at UKCEH, and find out about the many benefits of joining our team.
Every one of our 600+ staff and 50+ postgraduate students plays a vital role in delivering our ambition to understand the environment and the human impact on it, so that together people and nature can prosper.
How we work is just as important as what we achieve. We want UKCEH to be a welcoming, inclusive, engaging and collaborative place to work. We embed our values - excellence, integrity and teamwork - into everything we do.

Your main responsibilities will include:

• Conducting a cross-sectoral risk and vulnerability assessment, inspired by similar conducted under other projects (e.g., as described in Dunford et al. 2014)
• Working with an interdisciplinary team to adapt the methodology for the assessment based on unique considerations in the DISTENDER project
• Generating scenario-specific coping capacity maps for case studies underpinned by human, social, manufacturing and financial capital indicators and datasets
• Translating climate adaptation and mitigation strategies identified by case studies into quantitative terms for spatial analysis
• Overlaying outputs of other sectoral impact models with coping capacity maps to generate risk & vulnerability maps
• Using R (or Python) to automate analyses to produce outputs
• Interpreting and synthesizing outputs of the assessment for scientific publication

For the role of Spatial Data Scientist, we’re looking for somebody who has:

• A PhD or equivalent experience in environmental science or related topic, with a focus on spatial data analysis
• Experience using R (or Python) for spatial data analysis for the automation of analyses
• Experience translating qualitative information into quantitative representation for modelling
• Knowledge and experience working with large spatial datasets
• Interest in working with both quantitative and qualitative data (Desirable)
• Understanding and/or experience of methods and tools of scenario development (Desirable)
• Proven publication skills (Desirable