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- Tasks: Enhance pricing models using GLM techniques and machine learning.
- Company: Global insurance firm with a focus on innovation.
- Benefits: Hybrid work environment, significant career growth, and competitive salary.
- Why this job: Join a dynamic team and make an impact in the insurance industry.
- Qualifications: Experience with large datasets and knowledge of statistical modeling.
- Other info: Opportunity to work with advanced ML tools like Python and Emblem.
The predicted salary is between 36000 - 60000 £ per year.
A global insurance firm is seeking a talented technical GI pricing analyst to enhance pricing models within their home pricing team. This role involves using GLM techniques and machine learning with tools like Python and Emblem.
The right candidate will have experience with large datasets and strong knowledge of statistical modeling methods. This position offers the chance for significant career growth and the opportunity to work in a hybrid environment across the UK.
Home Pricing Analyst — Grow with Advanced ML & GLMs in London employer: Actuarial Futures
Contact Detail:
Actuarial Futures Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Home Pricing Analyst — Grow with Advanced ML & GLMs in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the insurance and pricing analysis field on LinkedIn. Join relevant groups and engage in discussions to get your name out there and learn about potential job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your experience with GLM techniques, machine learning, and any projects using Python or Emblem. This will give you an edge and demonstrate your capabilities to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on statistical modelling methods and be ready to discuss how you've applied them in real-world scenarios. Practice common interview questions related to pricing analysis to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! We often have exclusive listings that might not be found elsewhere. Plus, it shows you're genuinely interested in joining our team and helps us keep track of your application.
We think you need these skills to ace Home Pricing Analyst — Grow with Advanced ML & GLMs in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with GLM techniques and machine learning. We want to see how your skills align with the role, so don’t be shy about showcasing your work with Python and Emblem!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about pricing models and how your background makes you a perfect fit for our home pricing team. Let us know what excites you about this opportunity!
Showcase Your Data Skills: Since this role involves working with large datasets, make sure to mention any relevant projects or experiences. We love seeing how you’ve tackled data challenges in the past, so give us the details!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Actuarial Futures
✨Know Your GLMs Inside Out
Make sure you brush up on Generalised Linear Models (GLMs) before the interview. Be ready to discuss how you've applied these techniques in past projects, and think of specific examples where your modelling skills made a difference.
✨Show Off Your Python Skills
Since this role involves using Python, be prepared to talk about your experience with it. Bring up any relevant projects where you used Python for data analysis or machine learning, and if possible, mention any libraries you’re familiar with that are particularly useful in pricing analysis.
✨Demonstrate Your Data Handling Expertise
The job requires working with large datasets, so highlight your experience in managing and analysing big data. Discuss any tools or techniques you’ve used to clean, manipulate, and extract insights from large datasets, as this will show your technical prowess.
✨Prepare Questions About Career Growth
This position offers significant career growth, so come prepared with questions about development opportunities within the company. This shows your enthusiasm for the role and your desire to grow, which is something employers love to see!
