Full-Time Ecosystems Analyst @ Peterborough, England, United Kingdom
Job Description
Who is JNCC?
We’re the environment’s best kept secret. Established in 1990, we’re the UK’s statutory advisor on issues affecting the natural environment across the UK and internationally. Our primary role is advising all four Governments of the UK. With most of our work being within Government, our public profile is low but our impact is high. Our combination of scientific and analytical excellence with deep knowledge of how to facilitate joint working across jurisdictions allows us to deliver a much-valued service to the UK and other governments.
What’s the role?
JNCC’s Ecosystems Analysis team brings together three key functions to provide scientific nature conservation advise to the governments of the UK, the devolved administrations and the UK overseas territories. Firstly, we run a suite of national species surveillance schemes in collaboration with a range of partner organisations, gathering data from citizen scientists on birds, bats, butterflies and plants using pre-determined sampling protocols, and on all other taxa from ad-hoc recording. Secondly, we work with earth observation data from satellite sensors, developing processing standards and methods to facilitate use of these data sources by our government and statutory nature conservation agency partners as well as using them ourselves for habitat mapping and natural capital assessments. Thirdly, we have an analytical and modelling capability, bringing together data on species, habitats and natural capital to inform policy making, implementation and monitoring in the UK and internationally. This is the part of the team where these roles sit.
As the post holder, you will use your analysis and modelling skills to help ensure that environmental decision making is based on the best possible evidence and data. Examples of the big policy areas that your work might feed into include designing and implementing a new system of agricultural subsidies following EU exit, helping develop monitoring strategies to assess progress against Defra’s 25 Year Environment Plan’s ambitious goal to improve the environment within a generation, and helping the UK’s Overseas Territories to understand the benefits they gain from their natural environment and manage it effectively.
You will work primarily with spatial datasets, mostly using scripting languages (e.g. R, Python) to develop efficient, repeatable methods and models, but also GIS packages (e.g. QGIS, ArcGIS) to inspect data and generate maps. As a team we use technologies such as R Markdown and GitHub to develop reproducible analytical pipelines, and we increasingly make use of the R Shiny package to develop interactive web apps to maximise the accessibility of our outputs to our customers. We’re keen to ensure our analysts have the hardware and software needed to get the job done, so in addition to capable laptops we have access to a range of cloud computing platforms for working with large datasets.
Examples of modelling approaches that we use within the team include:
- Species distribution modelling using ensemble modelling techniques to maximise the value of our species records.
- Natural capital modelling and mapping using environmental datasets and models such as InVEST, combined with qualitative data on management interventions and socio-economic aspects using methods such as Bayesian Belief Networks.
- Machine learning techniques to evaluate habitat condition using satellite imagery.
Who are we looking for?
People with strong technical skills in data analysis and statistical modelling, and the ability to communicate the outputs of that analysis clearly to inform decision making, including through the creation of graphics and maps. Positive and enthusiastic about the evidence, you’ll be happy to share it, willing to spend time adapting your presentation so that it can be understood by different users, and comfortable and open about uncertainty and levels of confidence in our data. Full details of the role are included in the job description.
Why JNCC?
We’re small enough (c.200 staff) that you’ll know everyone by name, but big enough that we have all the skills, resources and people you’ll need to get the job done. We are flexible and welcoming, and we focus on supporting our staff with the freedom and tools they need to get their jobs done. You will benefit from our inclusive and lively workplace culture, training and CPD opportunities, excellent holiday and pension benefits, as well as an exciting job in a unique environment.
Post Duties
- Carry out a variety of analyses, working with JNCC colleagues with specialist technical skills where appropriate.
- Maintain a current overview of relevant methods and research in analytics.
- Design and produce decision-support tools to aid data and model interpretation by a non-technical audience
- Maintain JNCC’s information asset standards, including data acquisition, establishing efficient processing chains (e.g. within R), and ensuring data are placed in suitable repositories.
- Project management within the team, focussing on projects that will require some analytical input.
Technical
To be a successful candidate you will be:
- Able to use R, Python, or a similar scripting language to manipulate data and automate processes. (Note that the team generally uses R, and there is an expectation that any team member will be able to provide quality control checks on code produced in the team.)
- Able to use GIS software and packages, including manipulating, interpreting and mapping datasets and spatial databases; automating functions and establishing links to databases.
Experience
To be a successful candidate you will have:
- A relevant degree or equivalent qualification.
- Relevant experience in applying analytical techniques to spatial problems (note that ecological experience is not required but may be helpful).
Behaviours
- Seeing the Big Picture
- Making Effective Decisions
- Communicating and Influencing
- Working Together
- Managing a Quality Service
Please see the CS Behaviours framework for more details at this grade:
