At a Glance
- Tasks: Join a team to analyse biodiversity data and develop innovative solutions.
- Company: UKCEH is a leading independent research institute focused on environmental science.
- Benefits: Enjoy 27 days annual leave, flexible working, and wellness perks like gym discounts.
- Why this job: Make a real impact on biodiversity while gaining valuable experience in data science.
- Qualifications: A degree in environmental sciences or relevant experience; basic R/Python skills required.
- Other info: Hybrid working model and a supportive training plan for career growth.
The predicted salary is between 30684 - 32563 £ per year.
Salary - £30,684-£32,563
If you think you are the right match for the following opportunity, apply after reading the complete description.
Hybrid working (50/50) Permanent Wallingford (Oxfordshire) based. We reserve the right to close this advert early if we find the right candidate, so we encourage you to apply early.
Join the UK Centre for Ecology & Hydrology (UKCEH). We are seeking an enthusiastic and innovative Research Associate Data Scientist to join the Biodiversity Monitoring and Analysis Group within the Biodiversity and Land Use Science Area, at Wallingford. The successful candidate will have experience in quantitative and computational methods, and a keen interest in the natural environment and data science.
In this role you will be working to collate and analyse data collected by professional and citizen scientists and helping to develop new systems to collect, analyse and curate biodiversity data. This is a fantastic opportunity to gain experience in a range of projects that intersect ecological research and data science developments, including collaborating with researchers across Europe. You will join a team of scientists that uses national datasets, data science methods, and AI-assisted hardware, to develop approaches to understand and model the impacts of environmental change on biodiversity, ecosystems and the services they provide.
As a Research Associate at UKCEH, you’ll be supported with a three-year training plan at the start of your career. As well as on-the-job training and self-guided learning, you’ll have access to traditional learning, such as online and in-person courses. Training allocations are up to 15% in year one and two, and up to 10% in year three. Training will cover:
- FAIR data management and Open Science.
- Version control, collaborative coding, unit testing, and R-package development.
- The use of high-performance computing (HPC) to support large scale analyses.
- The application of computer vision methods to biodiversity research.
Your main responsibilities will include:
- Innovate & code: Build and refine model code, data science tools, software, and hardware solutions, or other digital assets or research outputs for projects.
- Prepare formatted data or figures for reports and publications.
- Undertake directed data collation or analysis, preliminary research and development, or laboratory analysis, to produce various outputs for the wider project team.
Additional Responsibilities:
- Deliver scientific outputs: Drive the development of high-quality project reports, publications, and innovative methods.
- Problem-solve collaboratively: Actively suggest during team meetings. Contribute ideas and written content to funding proposals.
- Communicate science: share findings and present at internal & external meetings.
- Lead analysis: Propose and explain analytical strategies in meetings to advance project outcomes.
- Manage deliverables: Oversee project components, demonstrating budget awareness and delivering value to funders.
- Publish & curate: Act as lead author for datasets, model code, software, or digital assets—ensuring quality assurance and repository submission.
As a Research Associate Data Scientist, we’re looking for somebody who has:
- Graduate/Post-graduate (Masters) or equivalent qualification or sufficient relevant experience.
- A degree in the environmental sciences, or other experience that demonstrates an interest in the natural world.
- A basic understanding and experience of R and/or Python.
- Effective communicator to a range of audiences.
- Time management skills and attention to details.
- Work within agreed parameters to meet the responsibilities of your role.
- Able to identify key stakeholders/funders.
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. 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.
Working for UKCEH is rewarding. We appreciate the continuous dedication and contributions of our staff, which is why we provide a comprehensive benefits package that includes financial incentives and wellbeing-oriented perks, such as:
- 27 days annual leave (rising to 29 days after 5 years’ service) plus 3 days for Christmas closure.
- 10% employer pension contribution.
- Flexible and hybrid working arrangements (role dependant).
- Peer reward and recognition scheme.
- Dental insurance, gym/fitness discounts, retail discount portal.
- Enhanced maternity and paternity leave.
- 24-hour, 365-day support with physical, mental, social, health or financial issues and much more.
Apply today! If this opportunity resonates with you and aligns with your personal career goals, the team would love to receive your application. Please apply by submitting your CV along with a covering letter that highlights any qualifications, skills or experience you believe are relevant to this role.
At UKCEH, we are committed to fostering an inclusive and equitable workplace where everyone—regardless of background, identity, ability, or circumstance—has the opportunity to thrive. As a Disability Confident employer, we actively encourage applications from neurodivergent candidates and those with disabilities. We are happy to provide any adjustments or support you may need throughout the application process—please don’t hesitate to reach out. So, if you’re excited about this role but your experience doesn’t align perfectly with every requirement, we’d love to hear from you anyway. You may be just the right fit for this role or another within our wider team.
We welcome applications from international candidates; however, at present, we are unable to provide visa sponsorship for this role.
Research Associate Data Scientist employer: UK CENTER FOR ECOLOGY & HYDROLOGY
Contact Detail:
UK CENTER FOR ECOLOGY & HYDROLOGY Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Associate Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in biodiversity data science. Follow relevant journals, attend webinars, and engage with online communities to stay updated. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the ecology and data science sectors. Attend conferences or local meetups where you can connect with researchers and practitioners. Building these relationships can lead to valuable insights and potential referrals for the position.
✨Tip Number 3
Prepare to discuss your experience with R and Python in detail. Be ready to share specific projects where you've applied these skills, especially in relation to data analysis or environmental science. This will showcase your technical abilities and relevance to the role.
✨Tip Number 4
Demonstrate your problem-solving skills by thinking of innovative solutions to common challenges in biodiversity research. Consider how you would approach data collection and analysis differently, and be prepared to share these ideas during interviews to highlight your creativity.
We think you need these skills to ace Research Associate Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and environmental sciences. Emphasise any quantitative and computational methods you've used, as well as your familiarity with R and Python.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the organisation. Mention specific projects or experiences that demonstrate your interest in biodiversity and data analysis, and how they align with the responsibilities of the position.
Showcase Your Communication Skills: Since effective communication is key for this role, provide examples in your application of how you've successfully communicated complex scientific concepts to diverse audiences, whether through presentations, reports, or collaborative projects.
Highlight Your Problem-Solving Abilities: Discuss instances where you've contributed innovative ideas or solutions in team settings. This could include your involvement in funding proposals or collaborative research efforts, showcasing your ability to think critically and work as part of a team.
How to prepare for a job interview at UK CENTER FOR ECOLOGY & HYDROLOGY
✨Show Your Passion for the Environment
Make sure to express your enthusiasm for the natural world and biodiversity during the interview. Share any personal experiences or projects that highlight your interest in environmental sciences, as this will resonate well with the interviewers at UKCEH.
✨Demonstrate Your Technical Skills
Be prepared to discuss your experience with R and/or Python in detail. You might be asked to solve a coding problem or explain how you've used these tools in past projects, so brush up on your technical knowledge and be ready to showcase your skills.
✨Prepare for Collaborative Problem-Solving
Since the role involves teamwork and collaboration, think of examples where you've successfully worked with others to solve problems. Be ready to discuss how you contribute ideas in team settings and how you handle feedback.
✨Communicate Clearly and Effectively
As an effective communicator is essential for this role, practice explaining complex data science concepts in simple terms. Prepare to discuss how you would present findings to different audiences, ensuring clarity and engagement.