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- Tasks: Enhance climate risk models and develop innovative analytical tools.
- Company: Leading financial market research firm in Greater London.
- Benefits: Dynamic work environment focused on sustainable finance.
- Why this job: Make a real impact in climate risk modelling and sustainability.
- Qualifications: Advanced degree in environmental science and experience in climate modelling.
- Other info: Strong analytical skills and knowledge of geospatial data analysis required.
The predicted salary is between 36000 - 60000 £ per year.
A leading financial market research firm in Greater London seeks a Climate Data Scientist to enhance climate risk models and develop innovative analytical tools. The ideal candidate will have an advanced degree in environmental science and experience in climate modelling and machine learning.
Responsibilities include:
- Creating data models
- Coordinating product development
- Supporting client inquiries
This role offers a dynamic work environment focused on sustainable finance, requiring strong analytical skills and knowledge of geospatial data analysis.
Climate Data Scientist: AI-Driven Climate Risk Modeling in London employer: Institutional Shareholder Services Inc.
Contact Detail:
Institutional Shareholder Services Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Climate Data Scientist: AI-Driven Climate Risk Modeling in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the climate science and finance sectors on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show off your passion for climate risk modelling.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with machine learning and geospatial data analysis. We recommend practising common interview questions related to climate modelling to boost your confidence.
✨Tip Number 3
Showcase your projects! If you've worked on any innovative analytical tools or climate models, make sure to highlight them in your conversations. We love seeing real-world applications of your skills, so don’t hold back!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive opportunities listed there that you won’t find anywhere else. Let’s get you that Climate Data Scientist role!
We think you need these skills to ace Climate Data Scientist: AI-Driven Climate Risk Modeling in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your advanced degree in environmental science and any experience you have with climate modelling and machine learning. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific responsibilities mentioned in the job description. We love it when candidates connect their experiences directly to what we’re looking for, especially in areas like data models and client support.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and enthusiasm for the role.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the Climate Data Scientist position. We can’t wait to hear from you!
How to prepare for a job interview at Institutional Shareholder Services Inc.
✨Know Your Climate Models
Make sure you brush up on the latest climate modelling techniques and tools. Be ready to discuss your experience with machine learning in this context, as it’s crucial for the role. Prepare examples of how you've applied these models in real-world scenarios.
✨Showcase Your Analytical Skills
Since strong analytical skills are a must, think of specific instances where you've used data analysis to solve problems. Be prepared to explain your thought process and the impact of your findings on previous projects or client inquiries.
✨Familiarise Yourself with Geospatial Data
Understanding geospatial data analysis is key for this position. Brush up on relevant software and methodologies, and be ready to discuss how you've used geospatial data in your past work. This will show your potential employer that you’re well-equipped for the challenges ahead.
✨Engage with Sustainable Finance Concepts
Since the role focuses on sustainable finance, it’s important to demonstrate your knowledge in this area. Research current trends and challenges in sustainable finance and be prepared to discuss how your work can contribute to innovative solutions in this field.
