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- Tasks: Analyse climate data and build models to manage climate risk in financial services.
- Company: Join a mission-driven analytics team focused on tackling climate challenges in London.
- Benefits: Enjoy a flexible hybrid work model, competitive salary, and career growth opportunities.
- Why this job: Make a real impact on climate risk while working with cutting-edge datasets and tools.
- Qualifications: Experience in data science, proficiency in Python or R, and a degree in a quantitative field.
- Other info: Ideal for those passionate about climate science and geospatial analysis.
The predicted salary is between 28800 - 48000 £ per year.
We're looking for a talented Data Scientist / Senior Data Scientist with a passion for climate risk and geospatial data to join our clients growing analytics team in London. If you're excited about turning complex environmental datasets into actionable insights for the FS sector, we want to hear from you.
About the Role
In this role, you'll work at the intersection of climate science, geospatial analysis, and insurance risk modeling, helping their clients better understand and manage the impact of physical climate risk. You'll be building scalable models and tools that directly support underwriting, portfolio risk management, and strategic planning in a changing climate.
What You'll Do
- Analyse and model climate and natural catastrophe datasets (e.g. flood, wildfire, storm, sea-level rise)
- Work with large-scale geospatial data (satellite imagery, GIS layers, remote sensing)
- Apply machine learning techniques to identify risk patterns and trends
- Develop tools to visualise and interpret climate risk data for technical and non-technical audiences
- Collaborate with insurance and reinsurance clients on climate-related risk assessments
- Stay on top of the latest climate science and ESG regulations impacting the FS industry
What We're Looking For
- Experience in data science, ideally in climate, geospatial, or catastrophe risk
- Proficiency in Python, R, or similar, with experience using libraries e.g. pandas, scikit-learn
- Experience with climate models (e.g. CMIP6, ERA5) or catastrophe models is a strong plus
- Degree in a quantitative field: data science, climatology, environmental science, geoinformatics, or similar
Why Join Us?
- Be part of a mission-driven team tackling real-world climate challenges
- Work with industry-leading datasets and tools
- Flexible hybrid work model (central London office)
- Competitive salary, bonus, and benefits package
- Career growth opportunities in a rapidly expanding area of climate risk analytics
Data Scientist (Climate & Geospatial) employer: PureFuel
Contact Detail:
PureFuel Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Climate & Geospatial)
✨Tip Number 1
Familiarise yourself with the latest climate science and geospatial analysis techniques. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the climate risk and geospatial data fields. Attend relevant conferences or webinars, and connect with industry experts on platforms like LinkedIn to gain insights and potentially get referrals.
✨Tip Number 3
Showcase your practical experience with Python, R, and relevant libraries by working on personal projects or contributing to open-source initiatives. This hands-on experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss specific examples of how you've applied machine learning techniques to real-world problems. Being able to articulate your thought process and results will demonstrate your expertise and problem-solving skills.
We think you need these skills to ace Data Scientist (Climate & Geospatial)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in climate and geospatial analysis. Use specific examples of projects or roles where you've applied machine learning techniques or worked with large datasets.
Craft a Compelling Cover Letter: In your cover letter, express your passion for climate risk and how your skills align with the role. Mention any specific experiences that demonstrate your ability to analyse climate data and collaborate with clients in the financial services sector.
Showcase Technical Skills: Clearly outline your proficiency in programming languages like Python or R, and mention any relevant libraries you have used. If you have experience with climate models or geospatial tools, be sure to include that as well.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops related to climate science, data analytics, or ESG regulations. This shows your commitment to staying updated in a rapidly evolving field.
How to prepare for a job interview at PureFuel
✨Show Your Passion for Climate Science
Make sure to express your enthusiasm for climate risk and geospatial data during the interview. Share any personal projects or experiences that highlight your commitment to understanding and addressing climate challenges.
✨Demonstrate Technical Proficiency
Be prepared to discuss your experience with Python, R, and relevant libraries like pandas and scikit-learn. You might be asked to solve a technical problem or explain how you've applied these tools in past projects.
✨Familiarise Yourself with Relevant Models
Brush up on climate models such as CMIP6 and ERA5, as well as catastrophe models. Being able to discuss these models and their applications will show your depth of knowledge and readiness for the role.
✨Prepare for Scenario-Based Questions
Expect questions that assess your ability to analyse and interpret complex datasets. Think about how you would approach real-world scenarios involving climate risk and be ready to explain your thought process clearly.
