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- Tasks: Evaluate models and present findings on climate risk using advanced analytics.
- Company: Leading UK risk management firm focused on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact on climate risk strategies with cutting-edge technology.
- Qualifications: PhD in risk sciences, proficiency in Python, R, SQL, and machine learning experience.
- Other info: Collaborative environment with a focus on emerging technologies.
The predicted salary is between 48000 - 72000 £ per year.
A leading risk management firm in the UK seeks a candidate with a PhD in a risk sciences area to perform model evaluations and present findings to various audiences. The ideal candidate is proficient in Python, R, and SQL, with experience in machine learning techniques. They should have strong collaboration and presentation skills, as well as a keen interest in commercial catastrophe models and climate modeling data. This role offers an engaging opportunity to inform risk strategies with emerging technologies.
Climate Risk Scientist & ML Analytics Lead employer: Emerald Group Ltd
Contact Detail:
Emerald Group Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Climate Risk Scientist & ML Analytics Lead
✨Tip Number 1
Network like a pro! Reach out to professionals in the climate risk and machine learning fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects in Python, R, and SQL. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Practice your presentation skills! Since you'll be presenting findings to various audiences, rehearse explaining complex concepts in simple terms. This will help you communicate effectively during interviews.
✨Tip Number 4
Apply through our website! We make it easy for you to find and apply for roles that match your skills. Don’t miss out on opportunities by applying elsewhere—let’s get you that job!
We think you need these skills to ace Climate Risk Scientist & ML Analytics Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your PhD and relevant experience in risk sciences. We want to see how your skills in Python, R, and SQL shine through, so don’t hold back on showcasing your technical prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the Climate Risk Scientist & ML Analytics Lead role. Share your passion for climate modeling and how your machine learning experience can contribute to our risk strategies.
Showcase Collaboration Skills: Since this role involves presenting findings to various audiences, highlight any past experiences where you’ve successfully collaborated with teams or communicated complex ideas. We love seeing candidates who can work well with others!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Emerald Group Ltd
✨Know Your Models Inside Out
Make sure you’re well-versed in the machine learning techniques relevant to climate risk. Be prepared to discuss your previous model evaluations and how they can inform risk strategies. This shows not only your expertise but also your passion for the field.
✨Showcase Your Coding Skills
Since proficiency in Python, R, and SQL is key, brush up on your coding skills before the interview. You might be asked to solve a problem or explain your approach to data analysis. Practising coding challenges can help you feel more confident.
✨Prepare for Diverse Audiences
You’ll need to present findings to various audiences, so think about how you can tailor your communication style. Prepare examples of how you’ve successfully communicated complex information in the past, whether to technical teams or non-experts.
✨Demonstrate Collaboration Skills
Collaboration is crucial in this role, so be ready to share experiences where you worked effectively with others. Highlight any interdisciplinary projects you've been involved in, especially those that relate to climate modelling or risk management.
