FBS Data Scientist

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 Turn raw insurance data into actionable insights and deployable models that support pricing, underwriting, and business strategy decisions. We are looking for a skilled Data Scientist to bridge the gap between complex business requirements and efficient database design. You will create conceptual, logical, and physical data models that optimize storage, ensure data integrity, and scale seamlessly across our data warehouse and operational systems. Responsibilities 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 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. Supports preparation of internal/external, structured/unstructured data sets to build/rebuild/refresh predictive models Develop and maintain conceptual, logical, and physical data models for relational databases, data warehouses, and data lakes Implement best-practice data warehousing structures, including star schemas, snowflake schemas, fact tables, and dimension tables. Optimize queries, normalize/denormalize data schemas, and reduce redundancy to boost database performance Requirements 2+