Environmental Risk Modeller (27148)
Changes in climate patterns and natural environments represent a risk to future economic stability. As companies adapt their plans to mitigate these risk and reduce their own environmental impact, numerical modelling can help them make the right decisions. This established company are building on a successful history of applying mathematical modelling to environmental and economics scenarios. With their continued growth, a new opportunity has arisen for a bright Environmental Risk Modeller to join their team.
You will work with large and complex data sets, primarily focussed on modelling climate risks, quantifying impacts, deriving insights, and presenting results visually to stakeholders. Your expertise in modelling and environmental science will allow you to become a go-to person for these topics, and you will be a key contributor to the future evolution of the modelling suite.
You will need:
- A 1st or 2.1 degree in a relevant numerate discipline (at minimum a bachelor’s, but preferably a higher degree), plus mostly A*s and As at A-level (or equivalent)
- A strong understanding of climatology or other environmental sciences along with proven experience in applying mathematical modelling or data science techniques to those areas
- Ability to evaluate climate models outputs and published datasets to produce customised analytics
- Programming skills, preferably in Python, along with strong communication and presentation skills
- Full, existing, and unrestricted right to work in the UK
This is a great chance to further your career in environmental modelling, working with a bright team of colleagues helping make the future of business more sustainable. This role is predominantly based in the company’s Cambridge offices, but there is some scope for occasional hybrid working. A competitive salary and benefits package are on offer to the successful candidate.
Keywords: Environmental Risk, Business Risk, Climate Science, Mathematical Modelling, Data Science, Sustainability, Cambridge
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