TL;DR
Senior Insurance Data Scientist (Cybersecurity): Leading analytic and modeling initiatives that power cyber underwriting, pricing, and automation capabilities with an accent on transforming complex insurance, cyber risk, and external signals into robust risk scores, insights, and tools. Focus on driving data-driven risk selection and workflow automation at scale and helping underwriters grow profitably and safely.
Location: Any location, Switzerland
Company
Coalition is the world's first Active Insurance provider designed to help prevent digital risk before it strikes.
What you will do
- Analyze diverse datasets to uncover patterns that improve cyber risk selection and pricing.
- Develop, calibrate, and maintain statistical and machine learning models to assess cybersecurity risk.
- Build clear reports, dashboards, and monitoring to track underwriting efficiency and risk selection quality.
- Apply statistical techniques to evaluate and refine Coalition’s cyber risk assessment methodology.
- Identify and implement opportunities to automate underwriting workflows using advanced analytics.
- Serve as a technical lead and mentor within the underwriting data science space.
Requirements
- Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Actuarial Science, or related).
- 5+ years of experience in underwriting, quantitative analysis, or risk modeling in the insurance industry, ideally with cyber or specialty lines.
- Strong understanding of insurance underwriting, pricing, reserving, or risk management processes.
- Advanced SQL skills for querying complex, large-scale databases.
- Expertise in data manipulation and analysis using Python, R, or similar tools (Python preferred).
- Experience with data visualization and BI tools (e.g., Tableau, Power BI, Looker) and building dashboards.
Culture & Benefits
- 100% public healthcare coverage
- 20 paid holidays (statutory minimum)
- Annual home office stipend
- Statutory pension
- Mental & physical health wellness programs
- Competitive compensation and opportunity for advancement
