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- Tasks: Use AI/ML and data analysis to assess business profitability and explore growth opportunities.
- Company: Leading health insurer in Royal Tunbridge Wells with a focus on innovation.
- Benefits: Competitive salary, annual bonuses, and flexible working options.
- Why this job: Join a dynamic team and make a real impact in the health insurance sector.
- Qualifications: Strong skills in data analysis and risk modelling tools required.
- Other info: Exciting opportunity for career growth in a supportive environment.
The predicted salary is between 36000 - 60000 £ per year.
A leading health insurer in Royal Tunbridge Wells seeks a Risk Modelling Analyst to join its Technical Pricing Team. The role involves utilizing advanced data analysis and machine learning to evaluate business profitability and identify opportunities for portfolio expansion.
Candidates should demonstrate strong technical skills in data analysis, risk modelling tools, and the ability to present findings clearly.
This position offers a competitive salary, annual bonuses, and flexible working options.
Hybrid Risk Modelling Analyst – AI/ML, GLM & GBM in Royal Tunbridge Wells employer: AXA Health
Contact Detail:
AXA Health Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Hybrid Risk Modelling Analyst – AI/ML, GLM & GBM in Royal Tunbridge Wells
✨Tip Number 1
Network like a pro! Reach out to professionals in the health insurance and risk modelling fields. Use platforms like LinkedIn to connect with people who work at the company you're eyeing. A friendly chat can sometimes lead to insider info or even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data analysis projects, especially those involving AI/ML, GLM, and GBM. When you get the chance to chat with hiring managers, share your findings and how they can apply to their business profitability.
✨Tip Number 3
Practice makes perfect! Get ready for interviews by rehearsing common questions related to risk modelling and data analysis. We recommend doing mock interviews with friends or using online resources to boost your confidence and clarity.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive roles listed there that you won’t find anywhere else. Don’t miss out on your dream job!
We think you need these skills to ace Hybrid Risk Modelling Analyst – AI/ML, GLM & GBM in Royal Tunbridge Wells
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data analysis and risk modelling tools. We want to see how your skills align with the role, so don’t be shy about showcasing your technical prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background in AI/ML can contribute to our Technical Pricing Team. Keep it engaging and relevant!
Showcase Your Analytical Skills: In your application, include specific examples of how you've used advanced data analysis to drive business decisions. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at AXA Health
✨Know Your Data Tools
Make sure you brush up on your technical skills, especially in data analysis and risk modelling tools. Be prepared to discuss specific software or programming languages you've used, and how they relate to the role of a Risk Modelling Analyst.
✨Showcase Your Machine Learning Knowledge
Since the job involves AI/ML, be ready to explain your understanding of machine learning concepts. Prepare examples of how you've applied these techniques in past projects, and think about how they can be used to evaluate business profitability.
✨Prepare for Scenario Questions
Expect scenario-based questions that assess your problem-solving skills. Think about potential challenges in risk modelling and how you would approach them. This will show your analytical thinking and ability to adapt.
✨Communicate Clearly
As the role requires presenting findings, practice explaining complex data insights in simple terms. Use examples from your experience where you successfully communicated technical information to non-technical stakeholders.
