The Environment Agency are fully committed to having an inclusive workforce to reflect the communities we serve. We don’t just talk about diversity; we seek it, embrace it and live it, for the benefit of our staff, our communities and our environment.  

Are you passionate about using data to make real-word impact and ready to take on the challenge of making sense of complex environmental data to tell compelling stories about our water environment?  

Join the Environment Agency’s Natural Capital and Ecosystem Assessment (NCEA) Programme as an Evidence Advisor focussing on the analysis of data from our new water monitoring networks covering rivers, small streams, groundwater, lakes and estuaries and coasts. The EA’s NCEA programme is part of the wider Defra-led NCEA, a multi-agency programme gathering broad scale comprehensive data on our ecosystems to reveal their benefits for people and the economy, i.e. their natural capital. Your analyses in this role will provide evidence and insight that will ensure policy and decision makers consider the true value of nature, helping the UK meets its environmental, net zero, and biodiversity targets.  

Key Responsibilities: 

• Analyse a variety of environmental data from NCEA monitoring networks using statistical modelling techniques. 
• Collaborate with network designers to evaluate and assure that networks are unbiased and representative. 
• Communicate effectively with technical and non-technical stakeholders. 
• Engage with internal and external stakeholders to identify user needs and develop data products that reflect these.  
• Develop reproducible analytical pipelines to deliver open government licensed, analysed data and accessible data visualisations. 
• Integrate alternative datasets to support regional and trend analysis reporting. 
• Peer review data analysis from other team members

You will join the Data Analysis and Statistics team of the NCEA Programme and be supported by the Strategic Evidence Design and Assessment team, which ensures the best environmental evidence is at the heart of decision-making.

Working in a dispersed way, you can expected a friendly welcome and engaging work environment, We have a strong team dynamic, believe in staff development and embrace diversity.

Background & Knowledge: 

• Degree or higher qualification in a relevant discipline, e.g., data science, statistics or environmental science (incorporating data analysis and statistics training) 
• Experience analysing data and undertaking statistical modelling of environmental or ecological data, including a strong understanding of the complexities, dependencies, interactions and biases within such data 
• Experience of statistical model fitting and robustness testing 

Key Skills: 

• Ability to engage and collaborate with internal and external stakeholders  
• Strong proficiency in programming (preferably R) 
• Expertise in implementing best coding practices, including functions, control flow, version control through Git/GitHub (advantageous) and comprehensive quality assurance and documentation 
• Self-motivated with the ability to work independently with strong organisational skills, managing workloads, deadlines, and priorities effectively 
• Strong written and oral communication skills with technical and non-technical audiences
• Works well in a team environment committed to knowledge sharing and learning and development  
• Detail-oriented with a passion for data analysis and problem-solving 

This is a national role, with hybrid working. You are expected to travel for face-to-face meetings, usually held quarterly (frequency / location are flexible).

Everyone that joins us is required to undertake training and participant in incident response duties when the need to respond arises. Having an incident role is an essential part of working for the Environment Agency and an active way to support communities and prevent harm to the environment. Further information on incident response can be found within your candidate pack.

For further information contact Eleanor D'Arcy (eleanor.d'[email protected]).

Interviews will be conduced using Teams.

If you consent to being held on a reserve list, we'll hold your details for 6 months and may offer you an alternative post.