Data Scientist - P&C Insurance Modeling

As an Excess and Surplus (E&S) carrier, we face unique and interesting problems every day. We are looking for a skilled Data Scientist to join our RA&D team. The role will report to the Director of Data Science. Upland Capital Group, Inc. is an AM Best rated “A-” VIII specialty property/casualty insurer headquartered in Dallas, Texas. Through its wholly owned insurance carrier, Upland Specialty Insurance Company, the company markets, underwrites and services specialty insurance products in select markets to include excess transportation, construction casualty, excess casualty, primary general liability, excess public entity, professional liability errors and omissions as well as excess cyber liability. We focus on “old school” underwriting as a craft, add “new school” analytics and technology, and encourage a gritty, growth mindset among people called “we entrepreneurs.” At our Risk, Analytics, & Data (RA&D) team, we focus on Actuarial, Data Science, Data and Model Engineering, and Enterprise Risk Management functions. Our Actuarial and Data Science model environment and architecture is containerized, and we are cloud based, running on Azure. Our vision is to build highly automated and efficient processes to build, test, and deploy our models and products for enhancing actuarial, underwriting and claim insights with timely and relevant data-driven analytics and technology. We look to create models that require creative problem solving and a close collaboration with stakeholders across the organization, not limited by a ‘one size fits all’ mindset. Key Areas of Responsibilities: As a Data Scientist at Upland, you will perform analyses and build models to support decision-making for actuarial, underwriting, claims, and other functions across the organization. You will be encouraged to try new things that push Upland forward and expand your own skillset. As a member of a growing team you will help define and establish the Data Science function for the company. Other Essential Duties include but not limited: Translate business requirements from different stakeholders into actionable data science projects Curate modeling datasets using internal and external data sources Build, test, and deploy models and other analytics products using appropriate techniques Ensure robust processes are in place for model documentation, monitoring, and maintenance Research, learn, test, and apply new techniques for non-standard insurance problems Apply data and model privacy and security protocols with R&A Data and Model Engineering Experience, Education and Skills Required: 2+ years of technical experience in a data science, actuarial, or predictive modeling role in the insurance industry Basic understanding of P&C insurance industry Self-starter, quick learner, and creative problem solver that thrives in a flexible, fast-paced remote-work environment Proficiency in programming languages such as Python, R, and/or SQL Strong knowledge of a variety of techniques and the ability and interest to learn new techniques quickly such as Regression, Classification, Bayesian Modeling, Reinforcement Learning, Natural Language Processing, Price Optimization, and Large Language Models Preferred Experience, Education and Skills Required Experience in the end-to-end model creation and deployment process to improve product, pricing, reserving, underwriting, and claims in P&C insurance P&C insurance domain knowledge, especially knowledge in commercial lines insurance and E&S products Bachelor's or Master's degree in Mathematics, Statistics, Data Science, Actuarial Science, or related quantitative field Ability to create production quality code Experience with non-relational (NoSQL) databases and cloud environment (e.g. Azure, AWS) Experience with a fully containerized model architecture Knowledge of agile development practices using Git Experience with visualization tools such as Power BI, Shiny, Streamlit, etc.