At a Glance
- Tasks: Lead data management projects and conduct complex analyses for nature recovery.
- Company: Join a passionate national team at Natural England focused on quality technical delivery.
- Benefits: Enjoy competitive salary, professional development, and opportunities for impactful work.
- Other info: Dynamic role with excellent career growth and the chance to inspire change.
- Why this job: Make a real difference in environmental recovery through innovative data science.
- Qualifications: Experience in data analysis, project leadership, and coding in Python or R.
The predicted salary is between 54000 - 66000 £ per year.
Data Science Services (DSS) is part of the Analysis Directorate.
We are a large, national team and have broad skills including data science, analysis and statistics.
We are passionate about quality technical delivery and continuous improvement, using novel data science approaches to help everyone understand nature recovery.
The roles would be initially based in our Marine or terrestrial geospatial analysis and data management team with potential to lead on data management projects, including standardisation, metadata and licensing.
- Lead and oversee standard data and spatial analyses, carry out standard and complex analyses, to meet the evidence needs of a variety of Natural England, Defra group and other stakeholders
- Ensure project data standards, processes and systems are followed to ensure outputs are high-quality and robust (including through good documentation and automation) so that customer decisions and advice can be based on sound evidence and outputs can be reproduced.
- For projects where the role is leading, liaise with project managers and teams to establish project planning and resourcing so that projects are delivered efficiently, with appropriate resource and capability, to a high standard, and progress, risks and issues can be monitored.
- People leadership skills / experience in either a functional or line management context (Essential)
- Experience of planning and leading the delivery of projects (Essential)
• Data analysis skills including
- Data extraction/ingestion and preparation, exploratory data analysis, and data visualisation (Essential)
- Working with a range of large scale spatial and non-spatial data types in both structured and unstructured formats (Essential)
- Experience working with (preferably combining) a range of biological, geographical and social data (Essential)
- Experience of coding in Python, R and FME (Desirable)
- Experience in Machine Learning / Deep Learning applications (Desirable)
- Experience in GIS software (e. g. Arc Pro, Arc GIS, Arc GIS Online, QGIS) (Essential)
- Knowledge of relevant data/metadata standards (Essential)
- Understanding of good practice, ethics, and quality assurance for data analysis (Essential)
- Working with databases, web-based applications, open-source software and APIs (Essential)
- Experience of a range of statistical techniques and applications (e. g.
SAS, SPSS, R) for identifying relationships between data and for inference, parametric and non‑parametric analysis and methods for quantifying uncertainty. (Essential)
- Experience in designing or contributing to digital tools such as data‑collection apps, dashboards, or field‑data interfaces (Desirable)
- Technical/specialist knowledge
- Problem solving (Essential)
• Data analysis skills including
- Data extraction/ingestion and preparation, exploratory data analysis, and data visualisation (Essential)
- Working with a range of spatial and non-spatial data types (Essential)
- Experience working with biological, geographical and social data (Essential)
- Experience in geospatial software (e. g. Arc Pro, Arc GIS, Arc GIS Online, QGIS) (Essential)
- Knowledge of relevant data/metadata standards (Essential)
- Understanding of good practice, ethics, and quality assurance for data analysis (Essential)
- Experience of coding in R/Python, including use of Git Hub for robust version control (Desirable)
- Working with databases, web-based applications and APIs (Desirable)
- Experience of a range of statistical techniques and applications. (Essential)
- Understanding of habitat data and classification approaches in a UK context (Desirable)
- Handle data responsibly, understand your role in good governance and comply with delegations, policies and procedures (Practitioner)
- Manage and delivery your work to meet agreed targets and deadlines (Practitioner)
- Personal Effectiveness
- Be ambitious, identify and adopt ways to make improvements in your team and Natural England and inspire others to act (Practitioner)
- Share expertise and knowledge with people and networks so that you can develop together (Practitioner)
- Apply new technology to improve the way we deliver our work (Practitioner)
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Higher Data Scientist - ( Ref : 6726 ) employer: Natural England
Natural England is an excellent employer, offering a dynamic work environment where employees can contribute to vital ecological projects that impact the future of England's natural landscapes. With a strong emphasis on employee development and collaboration, team members benefit from opportunities for growth and learning while working alongside passionate professionals dedicated to conservation. The supportive culture and commitment to sustainability make this role not only meaningful but also rewarding for those looking to make a difference in the ecosystem.
