MGA platform accelerator, USA funded and taking the UK market by storm.
Building out a data centre of excellence, geared to offering P/C underwriters competitive data diagnostics to rate and price insurance risk, and optimise ROI.
About the Role Working in a small, growing team of specialists (underwriters, business and data analysts), you will work through a range of data analytics responsibilities including: Scoping data requirements Working with large data sets Cleansing, structuring and formatting data Modeling data Visualising data Developing a modern, competitive and AI led data analytics offering Non-negotiable requirement s - The role requires that you are: Eligible to work in the UK Open to hybrid work, with office based days specified Are a good fit for a small, highly visible, and genuinely fast paced environment Have pre-exiting insurance (underwriting) experience or knowledge that can be verified Qualifications A strong academic foundation (Honors degree level STEM, Data Analytics or similar) and acquired insurance (underwriting) experience - either via an Insurance Risk Management degree, CII accreditation or working experience within a general insurer, carrier, MGA, Lloyd's.
Circa 4+ years related business data analysis experience, gained within an insurance carrier, intermediary, an insurtech or insurance consulting environment Excellent client facing communication skills, and ability to translate these into req docs as part of a full lifecycle analyst function Required Skills Strong capabilities in requirements elicitation and clarification (business analysis) Experience working with SQL, Excel, Python or R. Skills in the use of Data visualisation tools (Qlikview, Tableau or Power BI) Understanding of / experience in the insurance underwriting lifecycle, and key data metrics that support risk rating, pricing, performance metrics Preferred Skills Further experience in the use of Azure Data Factory would be highly favored, but is not a core requirement.
To apply for this role, please send over an up to date copy of your CV to ******