Ecological Statistician

Gold Group; City Of London; Remote; GBP 45,000 - 65,000; Full time

Job summary

Gold Group is seeking a highly skilled statistician for the LTEC programme to lead complex analyses of long-term ecological data. The role focuses on understanding biodiversity changes, climate and air pollution impacts, and informing policy-relevant conclusions.

The successful candidate will apply ecological statistics, design experiments, and communicate findings clearly to diverse audiences, while delivering timely results within a UK remote-working setup.

Qualifications

• Degree in statistics, ecology or a closely related field (essential).
• Experience with experimental/survey design and related statistical analyses (essential).
• Experience with ecological statistics and data interpretation (essential).
• Experience with statistical techniques in R or Python for multivariate relationships and uncertainty (essential).
• Ability to communicate complex information to varied audiences (desirable).
• Ability to manage work to meet targets and deadlines (essential).

Responsibilities

• Provide statistical leadership for the LTEC programme and undertake complex analyses.
• Unlock value of long-term datasets through rigorous, iterative analysis.
• Analyse multi-pressure ecological datasets to identify causal drivers.
• Develop revised monitoring design to improve efficiency and statistical power.
• Retain core methodology to maximise use of existing data.

Skills

Statistical leadership

Long-term data analysis

R/Python

Experimental design

Data interpretation

Communication

Education

Degree in statistics / ecology

Tools

R

Python

SPSS

Job description

This role is fully remote, please only apply if you are currently located in the UK and have full right to work in the UK

Description of Role:

The Long-Term Ecosystem Change (LTEC) programme is part of our Monitoring Directorate. The primary objective of LTEC is to detect biodiversity change and identify the causes over an appropriate timescale, with the purpose of increasing understanding of the impact of different ecosystem pressures and their interactions on biodiversity. It is particularly focused on the impacts on climate change and air pollution and produces data that is important for statutory reporting. The evidence it produces is intended for use in conservation advice informing effective recovery of nature and potential policy changes

The LTEC programme is a strategically important, research initiative designed to address critical evidence gaps long-term, systematic data collection and analysis across 37 sites in England. The programme's success depends not only on data collection, but on robust statistical design and analysis to identify relationships between ecosystem pressures and observed biodiversity change-an area where uncertainty remains high and current understanding relies heavily on expert opinion rather than empirical, real-world evidence.

skills & requirements

Key Tasks

• Provide statistical leadership for the LTEC programme, undertaking complex statistical analysis to help meet its primary objectives.
• Unlock the value of long-term datasets by thorough rigorous, iterative analysis.
• Analysis of complex, multi-pressure ecological datasets, required to identify causal drivers of ecosystem change.
• Develop a revised monitoring design to reduce redundancy and increase statistical power, improving efficiency and ensuring that future data collection is efficient, targeted, and statistically robust.
• Revise the monitoring design to retain as much of the current methodology as possible, to facilitate maximum use of existing data.

Knowledge and Skills

• Experience of working in statistical and/or ecological or environmental fields, educated to degree level in a relevant subject or ability to demonstrate equivalent experience (essential).
• A good understanding of experimental/survey design and related statistical analyses; ideally experience in ecological statistics (essential).
• Able to evaluate comparative approaches to statistical analysis and monitoring design, examine implications and make justified and evidenced recommendations (desirable).
• Experience of a range of statistical techniques in R or Python (or SPSS) for examining relationships (including multivariate) between data and for inference, parametric and non-parametric analysis, and quantifying uncertainty (Essential).
• Experience of contributing to relevant scientific literature (including responsibility for statistical analysis) and/or relevant technical reports (desirable)
• Effective written and verbal communication skills, especially in conveying complex information, data, analytical methods, and results to a range of audiences (desirable).
• Manage and deliver your work to meet agreed targets and deadlines (essential).

Reporting publication list

Able to communicate complex information Ecological data Experience

ESSENTIAL: ecological statistical knowledge