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Insight Select

Exposure / Quantitative Data Analyst

Insight Select Bishopsgate
80,000 to 90,000
32 - 40 hour


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    Insight Select

    Exposure / Quantitative Data Analyst

    Insight Select Bishopsgate
    80,000 to 90,000
    32 - 40 hour
    Status Open
    Apply now

    Apply on the employer's website


    What we ask

    Education

    No minimum education required

    What we offer

    Salary
    £80,000 to £90,000
    Hours
    32 to 40 hours per week
    Employment type
    permanent

    Job description

    Exposure Data Analyst / Quantitative Exposure Analyst London | £80,000 - £90,000 + Benefits

    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
    Salary description

    £80000.00 - £90000.00 per year

    Apply now

    Apply on the employer's website

    Apply now

    Apply on the employer's website


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