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Casualty Pricing - Paris, France - SCOR Global Life
Description
This role would suit an Actuarial Analyst or a fresh graduate who would like to take the next step in their career and broaden their knowledge.
It provides the opportunity to work within a diverse, and growing pricing team who oversee a global book of Casualty and Financial Lines business.
SCOR, the 4th largest reinsurer in the world, provides insurance companies with a diversified and innovative range of solutions and services to control and manage risk.
Leveraging experience and expertise to deliver "The Art & Science of Risk", SCOR provides cutting-edge financial solutions, analytics tools and services in all areas related to risk - from Life & Health and Property & Casualty insurance to Investments.
Proven pricing experience in P&C insurance with recent Lloyd's / London / French / European Markets experience is desirable, but not compulsory.
Working knowledge of coding in R, Python, SQL and VBA.Knowledge of Git and DeepKube is a plus.Has a commercial outlook but with a principled stand where required and contributes to create viable and innovative solutions that outperform competitors and differentiates SCOR.Fluent in French and English.
Key duties and responsibilitiesLarge account pricingPre-process loss run and exposure data for large account pricing.Compare loss run between expiring and renewal, identify inconsistencies, reach out to underwriters for clarification and/or request for additional data.
Price large accounts using account's data, leverage portfolio level data if account's data is not credible.Gather account level data to compile portfolio level data, establish benchmark frequency, severity selection by class of business.
Develop, test, maintain and enhance pricing toolsMaintenance of pricing tools including technical documentation/specifications/parameter update.
Refresh, clean and prepare data from third party vendor for model input. Calibrate pricing tools, train/troubleshoot questions from underwriters. Build/maintain sql database to store rating parameters and pricing results. Maintain python code and pipeline on remote repository to automate downloading of policy data into sql database.
Connect sql database, DeepKube with Excel raters to allow data to flow back and forth. Migrate Excel raters to Underwriting Platform (UP).
