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- Tasks: Join a team to develop and maintain a bespoke modelling platform for analytics.
- Company: Global specialty insurance and reinsurance organisation with a collaborative culture.
- Benefits: Competitive salary, hands-on experience, and exposure to high-impact projects.
- Why this job: Make a real impact by building tools that support pricing and risk management.
- Qualifications: Degree in a quantitative field and experience with SQL and large datasets.
- Other info: Dynamic environment with opportunities to work closely with industry specialists.
The predicted salary is between 36000 - 60000 £ per year.
A global specialty insurance and reinsurance organisation is seeking an Analytics Platform Engineer to join a technical actuarial analytics development team. The team builds and maintains a bespoke modelling and analytics platform used to support pricing, loss modelling, and portfolio management across the business. This role is suited to someone with strong technical and mathematical skills who enjoys building tools, working with large datasets, and collaborating with actuarial and risk teams to deliver practical analytical solutions.
The Role
Reporting to a Senior Engineer, you will contribute to the design, implementation, and maintenance of software and processes that support a proprietary modelling platform. You will work closely with actuarial, exposure management, and project teams to translate requirements into reliable, maintainable systems and data pipelines.
Key Responsibilities
- Contribute to the development of a proprietary modelling and analytics platform, particularly the Back End calculation components
- Design and develop tools, reusable data pipelines, and datasets used in reporting and analysis
- Work with actuarial, risk, and business teams to understand requirements and deliver effective solutions
- Maintain and improve existing and legacy codebases
- Track development progress and maintain clear documentation
- Implement testing and controls to reduce operational risk
- Support the wider team with technical and analytical tasks as required
- Build domain knowledge in insurance, reinsurance, and modelling
- Stay current with modern engineering tools and practices
Skills and Experience
- Degree in Software Engineering, Mathematics, Physics, or a related quantitative discipline
- Around 3+ years' experience in insurance, reinsurance, or another data-intensive environment
- Experience working with SQL and large datasets (Microsoft SQL Server, Azure or similar preferred)
- Experience working with version control in a team environment (Git preferred)
- Exposure to parallelised or distributed computing environments
- Experience implementing mathematical or statistical methods in production systems
- Experience with Julia, Python, R, or similar languages
- Familiarity with actuarial or risk concepts is beneficial
- Ability to work in a collaborative, fast-paced environment
Working Environment
- Collaborative team working on complex modelling and analytics systems
- Opportunity to work closely with actuarial and risk specialists
- Exposure to high-impact analytical platforms used across the business
Actuarial Modelling Engineer employer: Spencer Rose Ltd
Contact Detail:
Spencer Rose Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Actuarial Modelling Engineer
✨Tip Number 1
Network like a pro! Reach out to professionals in the actuarial and analytics fields on LinkedIn. Join relevant groups and participate in discussions to get your name out there and show off your passion for the industry.
✨Tip Number 2
Prepare for those interviews! Research common questions for Actuarial Modelling Engineer roles and practice your answers. Don’t forget to showcase your technical skills and how you’ve tackled challenges in past projects.
✨Tip Number 3
Showcase your projects! If you've built tools or worked with large datasets, create a portfolio to demonstrate your skills. This can really set you apart from other candidates and give employers a taste of what you can do.
✨Tip Number 4
Apply through our website! We love seeing applications directly from our platform. It shows you're keen and makes it easier for us to track your application. Plus, you’ll be one step closer to joining our awesome team!
We think you need these skills to ace Actuarial Modelling Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Actuarial Modelling Engineer role. Highlight your technical and mathematical skills, especially any experience with SQL and large datasets, as these are key for us.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about actuarial analytics and how your background makes you a great fit for our team. Don’t forget to mention any relevant projects or tools you've worked on.
Showcase Your Technical Skills: In your application, be sure to highlight your experience with programming languages like Python or Julia. We love seeing examples of how you've implemented mathematical methods in production systems, so don’t hold back!
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 the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Spencer Rose Ltd
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in SQL and any programming languages mentioned in the job description like Python or R. Be ready to discuss your experience with large datasets and how you've used these tools in past projects.
✨Understand the Business Context
Familiarise yourself with the insurance and reinsurance industry. Knowing how actuarial modelling impacts pricing and portfolio management will help you connect your technical skills to the business needs during the interview.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex problems in previous roles. Think about specific challenges you faced while working with data pipelines or legacy codebases and how you resolved them.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s current projects or the technologies they use. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you.
