Lead Operations Research Data Scientist
4 months ago
Job Overview:
Chubb is seeking a highly skilled and experienced Operational Research Data Scientist to join our team. This critical role will be responsible for leading the optimization efforts for a new initiative, leveraging advanced OR techniques and AI technologies to solve core insurance problems dynamically. The ideal candidate will have a proven track record of delivering impactful optimization solutions and be an expert in the application of mathematical models to solve complex business problems.
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
• Lead 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
• Mentor and train junior data scientists to develop analytical skills in the team
• Stay up-to-date with the latest OR and AI techniques and explore innovative solutions to stay ahead of the competition
Qualifications:
• 10+ years of experience in the OR field with a strong understanding of the mathematical underpinning of optimization algorithms
• Advanced degree (Master’s or in Industrial Engineering, Operations Research, Applied Mathematics, or related fields
• Expertise in mathematical modeling, optimization, and simulation techniques
• Experience in deploying OR solutions in the cloud environment
• Experience 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
• Strong understanding of descriptive statistics and exploratory data analysis techniques
• Excellent 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
• Experience in leading end-to-end data science lifecycle from problem definition to model implementation
• Track record of successfully delivering impactful optimization projects in the insurance/finance/retail industries
• Ability to mentor and train junior data scientists to develop analytical skills in the team
• Self-driven with a passion for staying up-to-date with the latest OR and AI techniques and exploring innovative solutions to stay ahead of the competition.
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