Global P&C is an Allianz SE department established in 2011 as continuation of the Center of Competence project started in 2005. Its mission is supporting all Allianz P&C Entities to be outstanding in technical excellence by leveraging Allianz Capabilities.Global P&C Pricing team is responsible for identifying, supporting implementation and ensuring standards, best practices and guidelines for data management, tariff development, portfolio analysis and monitoring. Specifically, the team oversees :Joint projects with the Allianz local entities around the world : we collaborate with local entities on pricing projects concerning mainly technical pricing, behavioural models, price optimization, scenario analysis, development of pricing and portfolio management tools.Research and development on Data & Analytics and tools to enhance the level of sophistication always considering the business relevance and impactKnowledge sharing and training of best practices : we design and facilitate P&C Pricing Academy courses to the wide community of pricing analyst of Allianz Group.Review activities : periodically we review the full pricing process of each local entity to ensure the standardization and harmonization of pricing processes and the implementation of best practices across the group.KEY RESPONSIBILITIESSupport the data ingestion, transformation, cleaning and exploration proceduresStructuring data science solutions to achieve a given set of business objectivesBuild and prototype analysis and Machine Learning models and support their implementation and deployment in the systems of the companyModel customer’s behavior based on market and competitor’s analysisImplement and enhance dashboards and business intelligence tools to support risk analysis and portfolio managementDoing Research and Development to find new technical solutionsSummarize, design and communicate effectively the results to both internal and external stakeholdersAct as teacher for internal Pricing Academy coursesKEY REQUIREMENTS / SKILLS / EXPERIENCEPhD or Master’s degree in a quantitative field (e.g., Computer Science, Mathematics, Physics, Statistics or Engineering)Fluent in Italian and English, written and spokenWork experience (e.g. 1 year)Valued international experience in both academic and professional settingsProficient in Python programmingExperience with Pandas or SQL for data manipulation and analysisFamiliarity with machine learning techniques like gradient boosting machines and linear modelsExperience with PySpark for large-scale data processing would be an advantagePassionate and skilled in data analysis and statistical modelling to support strategic decisionsDemonstrated ability to work effectively as part of a diverse, multicultural and multidisciplinary teamJ-18808-Ljbffr
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