Operational Research Data Scientist

Job Responsibilities Develop and implement optimization models to improve business performance and operational efficiencies in the insurance industry Analyze large volumes of data and provide insights to make data-driven decisions for use in insurance risk profiling, claims management and other key problem areas Collaborate with cross-functional teams including actuaries, underwriters, and IT to design, develop, and integrate optimization solutions Participate in the end-to-end data science lifecycle from problem definition to model implementation Use AI algorithms and predictive modeling to create dynamic optimization models that can quickly adapt to changing market conditions and customer needs Stay up-to-date with the latest OR and AI techniques and explore innovative solutions to drive impactful optimization results Qualifications 3+ years of experience in the OR field with a strong understanding of mathematical modeling, optimization, and simulation techniques Bachelor’s degree in Industrial Engineering, Operations Research, Applied Mathematics, or related fields with advanced degree preferred Experience in deploying OR solutions in the cloud environment Familiarity with AI algorithms, predictive modeling and machine learning techniques and their application to insurance problem solving Proficiency in programming languages such as Python, R, and SQL Basic understanding of descriptive statistics and exploratory data analysis techniques Strong problem-solving and analytical skills with the ability to work with complex datasets Strong communication and collaboration skills to work effectively with different stakeholders and cross-functional teams Self-driven with an eagerness to learn and apply the latest OR and AI techniques to solve complex business problems #J-18808-Ljbffr Chubb