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- Tasks: Join our team to enhance risk models and collaborate on data-driven projects.
- Company: Be part of a leading Personal Lines Insurer with a focus on innovation.
- Benefits: Enjoy remote work flexibility with just 1-2 days in the office each month.
- Why this job: Make an impact through statistical modeling and machine learning in a supportive environment.
- Qualifications: 4+ years in general insurance, strong GLM expertise, and programming skills in Python or SQL.
- Other info: Opportunity to work with advanced tools like Radar and Emblem.
The predicted salary is between 48000 - 72000 £ per year.
I am working with a leading Personal Lines Insurer seeking a Principal/Lead Pricing Analyst within their technical (Home) team. The ideal candidate will have a strong model background and at least 4 years within the general insurance sector.
This role is largely remote with 1-2 days required per month.
Responsibilities:
- Contribute to planning and executing risk model updates, with a focus on continuous improvement in data and processes.
- Collaborate with various teams and stakeholders to understand their needs, data requirements, and anticipated modeling outcomes.
- Engage directly with data, from its source through modeling stages, and ultimately in rating implementation.
- Develop and validate statistical models and machine learning algorithms.
Requirements:
- Strong expertise in statistical modeling methods, particularly Generalised Linear Models (GLMs).
- Familiarity with machine learning techniques, especially Gradient Boosting Machines (GBMs).
- Proficient in programming languages such as Python, SQL, SAS, or similar.
- Experience with Willis Towers Watson software, such as Radar or Emblem.
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Principal Pricing - Technical employer: Arthur
Contact Detail:
Arthur Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Pricing - Technical
✨Tip Number 1
Make sure to highlight your experience with statistical modeling methods, especially Generalised Linear Models (GLMs), during any discussions or interviews. This will demonstrate your strong expertise in the area that is crucial for the role.
✨Tip Number 2
Familiarize yourself with the specific software mentioned in the job description, like Willis Towers Watson's Radar or Emblem. If you have experience with these tools, be ready to discuss how you've used them in past projects.
✨Tip Number 3
Since this role involves collaboration with various teams, prepare examples of how you've successfully worked with cross-functional teams in the past. This will show your ability to engage with stakeholders and understand their needs.
✨Tip Number 4
Brush up on your programming skills, particularly in Python, SQL, and SAS. Be prepared to discuss specific projects where you've applied these languages to solve problems or improve processes.
We think you need these skills to ace Principal Pricing - Technical
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience in the general insurance sector, particularly any roles that involved statistical modeling and machine learning. Detail your familiarity with Generalised Linear Models (GLMs) and Gradient Boosting Machines (GBMs).
Showcase Technical Skills: Clearly list your proficiency in programming languages such as Python, SQL, and SAS. If you have experience with Willis Towers Watson software like Radar or Emblem, be sure to mention it prominently.
Demonstrate Collaboration Abilities: Since the role involves working with various teams and stakeholders, provide examples of past collaborations. Highlight how you’ve engaged with different departments to understand their data needs and modeling outcomes.
Focus on Continuous Improvement: Discuss any initiatives you've taken in previous roles to improve data processes or model updates. This shows your commitment to continuous improvement, which is a key aspect of the job.
How to prepare for a job interview at Arthur
✨Showcase Your Technical Skills
Be prepared to discuss your experience with statistical modeling methods, especially Generalised Linear Models (GLMs) and machine learning techniques like Gradient Boosting Machines (GBMs). Bring examples of past projects where you successfully applied these skills.
✨Understand the Company’s Needs
Research the company and its products. Understand their approach to pricing and risk modeling. This will help you tailor your responses to demonstrate how your skills can meet their specific needs.
✨Prepare for Data-Driven Questions
Expect questions that require you to think critically about data. Be ready to explain how you engage with data from its source through modeling stages, and how you ensure accuracy in rating implementation.
✨Collaborative Mindset
Highlight your ability to collaborate with various teams and stakeholders. Share examples of how you've worked cross-functionally to understand data requirements and anticipated modeling outcomes.
