Zurich (Schaumburg, IL) seeks an Associate Data Scientist to apply advanced analytical techniques to complex data sets to develop distinctive analytical and risk insights that deliver improvements in business results and build optimal data sets to test hypotheses drawing from a broad mix of data sources. Specific job duties include: understanding and structuring business challenges and opportunities and contributing to the development of improvements to analytic techniques for insight generation; researching both internal and external data sources to determine value in solving business problems; probing the business and using internal and external data sources to generate testable hypotheses that lead to distinctive risk insights that can deliver improved business results; synthesizing distinctive analytical and risk insights into compelling ideas and messages; preparing internal/external, structured/unstructured data sets to build/rebuild/refresh predictive models; evaluating and quantifying project risks using predictive models and established methods to ensure that the business is not exposed to any undue risk; developing and tracking of key performance indicators of models and solutions to help insure solutions deliver intended business impact; implementing policy by following business processes, rules and guidelines to ensure adherence to the appropriate statutory and legal principles, and cords of conduct and industry guidelines; and effectively collaborating with team members, colleagues in technical underwriting and the business to help ensure the delivery of high quality products. Position requires occasional travel within the U.S.
Position requires a Master’s degree, or foreign equivalent, in Analytics, Data Science, Computer Science, Mathematics, or a closely related field of study, plus 3 years of experience in the job offered, or as a Strategy Analytics Lead, Intern, or similar position in the transforming data and developing insights for use in business decision area. Must have 2 years of experience with data tools such as Hive, Pig, SQL server, or similar. Specific experience must also include each of the following: applying data transformation techniques such as exact and probabilistic matching methods; statistical and predictive modeling techniques including GLM, machine learning, GBM, decision trees, and clustering; engaging business audience to identify issues and recommend solutions; using verbal and written communication skills to explain technical results for business audiences in a clear and concise manner; preparing data or developing insights for use in business decisions; and programming languages such as R, Python, SAS, Hive, Pig, or similar. Must be willing to occasionally travel within the U.S.Primary Location
Yes, 5 % of the TimeRelocation Available