At a Glance
- Tasks: Develop innovative tools for catastrophe exposure analytics and automate data processes.
- Company: Leading London Market insurer with a focus on exposure analytics.
- Benefits: Competitive salary, benefits package, and opportunities for professional growth.
- Other info: Collaborative team environment with exposure to senior stakeholders and advanced technologies.
- Why this job: Work on cutting-edge projects in risk management and automation while making a real impact.
- Qualifications: Experience in data analysis, strong Python and SQL skills, and knowledge of catastrophe modelling.
The predicted salary is between 80000 - 90000 £ per year.
Are you a data-driven insurance professional with strong Python and SQL skills looking to work at the forefront of exposure analytics, catastrophe risk, and process automation? I'm working with a highly regarded London Market insurer seeking an experienced Exposure Data Analyst / Quantitative Exposure Analyst to join a growing Exposure Management function. This is an excellent opportunity to combine technical expertise, data engineering, analytics and catastrophe risk management within a business where exposure analytics plays a central role in strategic decision-making.
The Role
Working closely with the Exposure Analytics Manager and wider Exposure Management team, you'll help develop innovative tools and analytical solutions that track, analyse and manage catastrophe exposure across the portfolio. This role offers significant exposure to modern technologies, automation initiatives, geospatial datasets, AI-driven solutions and advanced risk analytics, making it ideal for someone who enjoys solving complex problems and building scalable data solutions.
Key Responsibilities
- Develop and enhance analytical tools used to monitor natural catastrophe exposure across the business.
- Build automated data pipelines and reporting processes to improve efficiency and reduce manual workloads.
- Support the production of portfolio analytics and catastrophe exposure forecasts.
- Create and maintain dashboards and visualisation tools using platforms such as Power BI and Databricks.
- Work with research and underwriting teams to develop proprietary risk scoring datasets and portfolio insights.
- Develop Python and SQL solutions that improve catastrophe pricing and exposure management processes.
- Translate catastrophe model outputs into business-critical reporting used for capital modelling and portfolio management.
- Support data enrichment initiatives and explore emerging technologies, including AI-powered solutions.
- Collaborate with underwriters, actuaries and senior stakeholders to deliver meaningful exposure insights.
What We're Looking For
- Experience working within the insurance market in a data-focused analytical role.
- Exposure to Property insurance, catastrophe modelling or exposure management would be highly advantageous.
- Strong programming skills, particularly Python and SQL.
- Experience working with large datasets and process automation.
- Knowledge of catastrophe modelling platforms such as RMS or Verisk would be beneficial.
- Understanding of geospatial data, GIS tools or spatial analytics is desirable.
- Experience working with APIs, dashboarding tools and modern analytics platforms.
- Strong analytical and problem-solving skills with the ability to communicate complex findings clearly.
- A proactive, self-motivated approach and desire to improve processes through technology.
Why Apply?
- Join a business where exposure analytics is a key strategic function.
- Work on innovative projects involving catastrophe risk, automation, geospatial analytics and AI.
- Gain exposure to senior stakeholders and underwriting teams across the organisation.
- Be part of a collaborative, technically strong team environment.
- Excellent opportunity to develop both your technical and commercial expertise within the London Market.
For a confidential discussion and further information, please get in touch.
Exposure / Quantitative Data Analyst in London employer: Insight Select
Join a leading London Market insurer that prioritises exposure analytics as a core strategic function, offering a dynamic work environment where innovation thrives. With a strong focus on employee development, you will have the opportunity to enhance your technical skills in Python and SQL while collaborating with senior stakeholders on cutting-edge projects involving catastrophe risk and automation. Enjoy a supportive culture that values teamwork and encourages professional growth, making it an ideal place for data-driven professionals seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Exposure / Quantitative Data Analyst in London
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We think you need these skills to ace Exposure / Quantitative Data Analyst in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Insight Select. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Insight Select
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
