FBS - Data Scientist Predictive Analyst (Mid Level)

FBS – Farmer Business Services is part of Farmers operations with the purpose of building a global approach to identifying, recruiting, hiring, and retaining top talent. By combining international reach with US expertise, we build diverse and high-performing teams that are equipped to thrive in today’s competitive marketplace. We believe that the foundation of every successful business lies in having the right people with the right skills. That is where we come in—helping Farmers build a winning team that delivers consistent and sustainable results. Since we don’t have a local legal entity, we’ve partnered with Capgemini, which acts as the Employer of Record. Capgemini is responsible for managing local payroll and benefits. What to expect on your journey with us: A solid and innovative company with a strong market presence A dynamic, diverse, and multicultural work environment Leaders with deep market knowledge and strategic vision Continuous learning and development Team Function: Turn raw insurance data into actionable insights and deployable models that support pricing, underwriting, and business strategy decisions. Role Description: Help support Auto and Home Actuarial team update Base Rate Offset tool into Python. This role requires strong Python skills as well as self-learning skills. Contributes to the development and implementation of predictive analytics through the application of advanced statistical and analytical techniques in order to deliver data driven insights supporting business objectives. Uses appropriate modeling techniques to address business needs. Utilizes broad knowledge of advanced modeling techniques and procedures to develop new modeling techniques and skills. Conducts appropriate evaluation of model performance. Designs and publishes reports to communicate results and track model performance. Develops various programs including predictor and response variable programs. Reviews programs to ensure they conform to quality standards. Supports preparation of internal/external, structured/unstructured data sets to build/rebuild/refresh predictive models. Creates ad-hoc data analyses, as needed Communicates analytics to other modelers as well as to non-technical business partners. Contributes to the continuous improvement of the modeling process. Contributes to the continuous improvement of the modeling process.