FBS Data Scientist (Customer & Agent Solutions)

Our Client is one of the United States’ largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, our Client is part of one the largest Insurance Groups in the world.

About the Role The Data Scientist will be responsible for developing predictive models, advanced analytics solutions, and actionable insights that support strategic decision-making across Customer & Agent Solutions (CAS). This role partners closely with business stakeholders to identify opportunities, solve complex business problems, and drive measurable improvements in customer retention, agent experience, operational efficiency, and overall business performance. The ideal candidate combines strong technical expertise in machine learning, statistics, Python, and SQL with the ability to communicate insights to non-technical audiences and influence business outcomes.

Key Responsibilities Develop and deploy predictive and prescriptive analytics models to support customer and agent-related business initiatives. Apply machine learning, statistical analysis, and data mining techniques to solve complex business problems. Analyze large datasets to uncover trends, opportunities, and actionable recommendations. Design, build, and maintain scalable, production-ready analytical solutions. Partner with business stakeholders to translate business objectives into analytical approaches and success metrics. Collaborate with Data Engineering, IT, and Analytics teams on model deployment and optimization. Utilize ML Ops best practices, version control, and code documentation standards. Present findings and recommendations to technical and non-technical audiences. Support business areas focused on customer retention, servicing, operational performance, lead optimization, and agent effectiveness. Mentor junior team members and contribute to analytics best practices.