Analyst I (Bogotá)...

Are you passionate about pricing in the Insurance Industry? Would you like to join a dedicated team responsible for deploying pricing programs across all our retail lines in United States? This is then your next job! The USDS Pricing Deployments Team is looking for Data Science Analyst I, Analyst II or Assistant Director to design and build major pricing and underwriting programs in Earnix. This role will drive best practices within Earnix, while coordinating with modeling, data and technology teams to drive successful Earnix transformations, ultimately increasing speed to market and deploying more sophisticated models across lines of business.Key ResponsibilitiesDesign and build US Data Science pricing programs in Earnix.Assist on designing best-in-class capabilities to support post-modeling activities, including calibration, dislocation, and filing.Ensure accuracy of all pricing and non-pricing outputs from EarnixCoordinate planning and execution with our partner teams in Technology, Experience, Modeling Data Solutions and Data Office with understanding of the rating architectureAssist on designing and maintaining rigorous data models for Earnix analytical projects and API.Assist on designing and implementing other use cases of Earnix as a rating engine or an analytical tool.As required, troubleshoot and support post launch queries and issues.Adopt transformational mindset to improve and automate processes where applicable.Regularly engages with the data science community and participates in cross-functional working groups.About US Data ScienceUSDS employs more than 350 full-time professionals who build advanced data science products and AI solutions for our US Retail Markets (USRM) business. By thoughtfully applying data science across USRM functions, we ensure we consistently deliver on our promises while driving sustainable growth across our portfolio. We accomplish this through a focus on model development, deployment, and decision science. In model development, we design sophisticated models that combine deep data science expertise with close collaboration across our go-to-market verticals. This integration ensures our models not only incorporate cutting-edge science but, more importantly, generate measurable business value aligned with each vertical's strategic goals.Skills and ExperienceSolid knowledge of predictive analytics techniques and statistical diagnostics of models.Intermediate knowledge of predictive toolset; expert resource for automation scripts development; Python skills preferred.Strong understanding of rating algorithm structures, including their components, inputs, and outputs, is highly preferred.Knowledge of Earnix or similar rating tools knowledge is a plus.Demonstrated ability to exchange ideas and convey complex information clearly and concisely.A value-driven perspective with regard to understanding of work context and impact.Demonstrate business professional proficiency in English with excellent written and verbal communication skills.Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience, a Master's degree (scientific field of study) and 1+ years of relevant experience or may be acquired through a Bachelor's degree (scientific field of study) and 3+ years of relevant experience. #J Ljbffr

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