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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: Engaging role with opportunities to influence risk strategies and use emerging technologies.
- Why this job: Make a real impact on climate risk management while working with cutting-edge tools.
- Qualifications: PhD in risk sciences, proficiency in Python, R, SQL, and machine learning experience.
- Other info: Collaborative environment with a focus on professional growth and development.
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 in London 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 in London
✨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 and show off your expertise.
✨Tip Number 2
Prepare for interviews by practising your presentation skills. Since you'll be presenting findings to various audiences, make sure you can explain complex concepts in simple terms. Use mock interviews with friends or mentors to refine your delivery.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your work with Python, R, and SQL, especially any machine learning models you've developed. This will give potential employers a tangible sense of your skills and experience.
✨Tip Number 4
Don't forget to apply through our website! We have loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to stay updated on new roles and company news.
We think you need these skills to ace Climate Risk Scientist & ML Analytics Lead in London
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 modelling and how your machine learning experience can contribute to our risk strategies.
Showcase Collaboration Skills: We value teamwork, so highlight any past experiences where you’ve successfully collaborated with others. Whether it’s presenting findings or working on projects, let us know how you’ve made an impact in a team setting.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your materials and ensures you’re considered for this exciting opportunity. We can’t wait to hear from you!
How to prepare for a job interview at Emerald Group Ltd.
✨Know Your Models
Make sure you’re well-versed in the latest machine learning techniques and climate modelling data. Be prepared to discuss specific models you've worked on, how you evaluated them, and the impact of your findings. This will show your depth of knowledge and 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 code. Practising common algorithms or data manipulation tasks can give you an edge.
✨Prepare for Diverse Audiences
You’ll need to present your findings to various audiences, so practice explaining complex concepts in simple terms. Tailor your explanations to different levels of understanding, whether you're talking to technical experts or non-specialists. This will demonstrate your strong presentation skills.
✨Collaborate and Connect
Highlight your collaboration experience during the interview. Share examples of how you’ve worked with cross-functional teams or contributed to group projects. This will show that you’re not just a lone wolf but someone who thrives in a team environment, which is crucial for this role.
