• Build and maintain dashboards and MI to monitor underwriting controls and support audits.
• Automate and manage reporting for underwriting class and product leaders.
• Investigate underwriting performance queries and provide actionable insights.
• Design, develop, and validate predictive models to inform underwriting decisions.
• Work with data engineering teams to design and maintain Azure Databricks pipelines.
• Support the automation of data-driven deliverables for proactive services.
• Identify and resolve data issues, recommending fixes and improvements.
• Collaborate with underwriters, actuaries, and operations teams to embed insights into strategy and decision-making.
• Present findings through clear dashboards, presentations, and reports tailored to both technical and non-technical audiences.
• Stay ahead of emerging tools, techniques, and best practices in data, ML, and AI.
What we re looking for
• A background in data science or advanced analytics (insurance/financial risk exposure is a plus).
• Strong Python and SQL skills, with experience working with large structured and unstructured datasets.
• Experience building interactive dashboards and reporting tools.
• Familiarity with data engineering, ETL processes, and data pipelines.
• Experience with statistical modelling and machine learning techniques, and libraries such as scikit-learn, PyTorch, or TensorFlow.
• Excellent communication skills able to explain complex analysis to non-technical stakeholders.
• Proactive, inquisitive mindset with strong problem-solving skills.
• Interest in cyber risk and awareness of emerging trends in the space.
• Be part of a growing global team driving innovation in cyber analytics.
• Work with modern data platforms and cutting-edge analytics techniques.
• Make a tangible impact on underwriting performance and business strategy.
• Opportunity to develop your career in the intersection of cyber risk, data science, and insurance analytics.