What are the responsibilities and job description for the Analyst, Data Science: Property & Specialty Product Design & Modeling position at Liberty Mutual Insurance Group?
Assist on design of designing pricing programs deployment pipeline from modelling to product launch in coordination with the Deployments team Identifies areas for potential process improvements and implements necessary changes to bring products speed to market accurately and efficiently Collaborates within the team to successfully implement new pricing programs as desired Evaluates and verifies the outputs and processes, promptly communicating any issues that may arise Develop line-of-business expertise for the property and specialty pricing and underwriting programs Applies knowledge of sophisticated analytical techniques to manipulate structured and unstructured datasets for generating insights to inform business decisions Translates quantitative analyses and findings into accessible visuals for non-technical audiences and effectively communicate those in written, oral, and presentation formats Supports other property and specialty pricing programs including building models and rollouts with adjusting models due to state restrictions, building supporting documents and responding to DOI objections Regularly engages with the data science community and participates in cross-functional working groups Have proficient level of knowledge with predictive modeling software (e.g., Emblem, Radar) and with Python, including the ability to support and develop related packages. Have a strong understanding of rating algorithm structures, including their components, inputs, and outputs Data extraction and manipulation skills, EDA, transformations, and general linear models (GLM); preferred skills of basic CART and GLM. Foundational knowledge of predictive analytics tools. Demonstrated ability to exchange ideas and convey complex information clearly and concisely. Has a value driven perspective with regard to understanding of work context and impact. Competencies typically acquired through a Master`s degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and no professional experience or may be acquired through a Bachelor`s degree and 3 years of relevant experience.