Data Analyst

Brief DescriptionRole Overview The Data Analyst will be responsible for analysing large datasets related to underwriting, claims, bordereaux, and financial performance, providing actionable insights to management, underwriting teams, and capacity providers. The role requires strong analytical acumen, attention to detail, and an understanding of insurance/reinsurance data flows, including exposure modelling, premium tracking, and loss ratios. Key Responsibilities • Collect, clean, and validate data from multiple internal and external sources including underwriting systems, bordereaux submissions, reinsurer reports, and claims databases. • Develop and maintain automated dashboards and performance reports (e.g., premium income, claims ratio, renewal trends, retention metrics). • Perform portfolio and treaty-level analysis to identify patterns, profitability drivers, and underwriting performance by class of business. • Support reinsurance data submissions, risk aggregation, and exposure modelling to ensure accuracy and timeliness. • Work with the Finance and Underwriting teams to reconcile financial and operational data, ensuring consistency across systems. • Assist in quarterly MI packs, regulatory submissions, and broker or capacity provider reporting. • Analyse cost per lead, conversion ratios, and other distribution metrics for the MGA’s retail and commercial lines. • Collaborate with IT to optimise data pipelines and improve reporting automation. • Present findings and recommendations to senior management and board-level committees in a concise, insight-driven format.Preferred SkillsKey Skills & Competencies • Strong analytical, numerical, and problem-solving skills. • Proficiency in SQL, Power BI / Tableau, and Excel (advanced). • Working knowledge of Python or R for statistical modelling or automation (preferred). • Understanding of insurance concepts — premium, claims, loss ratio, exposure, treaty vs. facultative, etc. • Familiarity with bordereaux management, regulatory reporting (FCA, Lloyd’s, or PRA) and reinsurance data structures. • Excellent attention to detail with the ability to manage multiple projects and deadlines. • Strong communication skills — able to present complex data clearly to non-technical stakeholders. Qualifications & Experience • Degree in Data Science, Statistics, Finance, Actuarial Science, or a related field. • Minimum 2–4 years of experience as a Data Analyst in insurance, reinsurance, or MGA sectors. • Experience with data visualisation tools and ETL processes. • Familiarity with regulatory or Lloyd’s MI reporting is a plus