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Consultants for various and unanticipated worksites throughout the U.S (HQ: Chicago, IL). Partner with internal and external cross-functional teams to drive new business initiatives and deliver long term value-added product propositions for business customers in the US and international insurance segments. Lead the development of predictive models and business intelligence solutions for insurance carriers. Manage the Insurance Analytics team’s analytical engagements supporting International Insurance Vertical. Coordinate all analytical efforts to bring a variety of insurance underwriting, rating, application fraud, and other point-of-quote/bind solutions to major international markets including Canada, South Africa, India, Hong Kong, Mexico, and other Latin America countries. Work closely with product and business development counterparts in international insurance markets to support implementation of product “Lift-and-Shift” strategy. Explore internal/external data sources for each market to create innovative new products to be implemented at a variety of insurance carriers. Independently lead data analysis and modeling projects from project design, business review meetings to derive requirements, reception and processing of data, performing analyses and modeling, to final reports/presentations, communication of results, and sales support. Utilize advanced statistical techniques and insurance business knowledge to create high-performing predictive models and creative analyses to address business objectives and client needs. Proactively and effectively communicate in various verbal and written formats with internal stakeholders on product design, data specification, model implementations, with partners on collaboration ideas and specifics, and with clients on project/test results, opportunities and questions. Act as an insurance analytics expert on meetings with clients and partner companies. Provide mentorship and training to junior colleagues and maintain progress on all initiatives under minimal direct supervision. Technical environment: Python (numpy, pandas, matplotlib, scikit-learn), R (ggplot2, dplyr, tidymodels, sparklyr), SAS, SQL, Hive, Git, Bash, Tableau, Jupyter Notebook, RStudio, AWS, bias mitigation techniques (BISG/BIRDie/SMD), statistical modeling techniques (linear regression, logistic regression, GLM, neural network, GBM, tree models, cluster analysis, principal components, and feature creating and validation) risk modeling for insurance.Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, Fair Chance Initiative for Hiring Ordinance, and the California Fair Chance Act.
Adherence to Company policies, sound judgment and trustworthiness, working safely, communicating respectfully, and safeguarding business operations, confidential and proprietary information, and the Company’s reputation are also essential expectations of this position.
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